Plenary Speech: Researching Complex Dynamic Systems--"Retrodictive Qualitative Modelling" in the Language Classroom

ERIC Educational Resources Information Center

Dörnyei, Zoltán

2014-01-01

While approaching second language acquisition from a complex dynamic systems perspective makes a lot of intuitive sense, it is difficult for a number of reasons to operationalise such a dynamic approach in research terms. For example, the most common research paradigms in the social sciences tend to examine variables in relative isolation rather…

Complexity Leadership: A Theoretical Perspective

ERIC Educational Resources Information Center

Baltaci, Ali; Balci, Ali

2017-01-01

Complex systems are social networks composed of interactive employees interconnected through collaborative, dynamic ties such as shared goals, perspectives and needs. Complex systems are largely based on "the complex system theory". The complex system theory focuses mainly on finding out and developing strategies and behaviours that…

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties

PubMed Central

Zapata-Fonseca, Leonardo; Dotov, Dobromir; Fossion, Ruben; Froese, Tom

2016-01-01

There is a growing consensus that a fuller understanding of social cognition depends on more systematic studies of real-time social interaction. Such studies require methods that can deal with the complex dynamics taking place at multiple interdependent temporal and spatial scales, spanning sub-personal, personal, and dyadic levels of analysis. We demonstrate the value of adopting an extended multi-scale approach by re-analyzing movement time-series generated in a study of embodied dyadic interaction in a minimal virtual reality environment (a perceptual crossing experiment). Reduced movement variability revealed an interdependence between social awareness and social coordination that cannot be accounted for by either subjective or objective factors alone: it picks out interactions in which subjective and objective conditions are convergent (i.e., elevated coordination is perceived as clearly social, and impaired coordination is perceived as socially ambiguous). This finding is consistent with the claim that interpersonal interaction can be partially constitutive of direct social perception. Clustering statistics (Allan Factor) of salient events revealed fractal scaling. Complexity matching defined as the similarity between these scaling laws was significantly more pronounced in pairs of participants as compared to surrogate dyads. This further highlights the multi-scale and distributed character of social interaction and extends previous complexity matching results from dyadic conversation to non-verbal social interaction dynamics. Trials with successful joint interaction were also associated with an increase in local coordination. Consequently, a local coordination pattern emerges on the background of complex dyadic interactions in the PCE task and makes joint successful performance possible. PMID:28018274

Structural actions toward HIV/AIDS prevention in Cartagena, Colombia: a qualitative study.

PubMed

Quevedo-Gómez, María Cristina; Krumeich, Anja; Abadía-Barrero, César Ernesto; Pastrana-Salcedo, Eduardo Manuel; van den Borne, Hubertus

2011-07-01

To obtain a thorough understanding of the complexity and dynamics of the social determination of HIV infection among inhabitants of Cartagena, Colombia, as well as their views on necessary actions and priorities. In a five-year ethnography of HIV/AIDS in collaboration with 96 citizens of Cartagena, different methods and data collection techniques were used. Through 40 in-depth interviews and 30 life histories of inhabitants, the scenario of HIV vulnerability was summarized in a diagram. This diagram was evaluated and complemented through group discussions with key representatives of local governmental and nongovernmental organizations and with people who were interested in the epidemic or affected by it. The diagram illustrates the dynamic and complex interrelationships among structural factors (i.e., social determinants) of HIV infection, such as machismo; lack of work, money, and social services; local dynamics of the performance of the state; and international dynamics of the sexual tourism industry. On the basis of the diagram, groups of key representatives proposed prioritizing structural actions such as reducing socioeconomic inequalities and providing access to health care and education. The social determinants displayed in the diagram relate to historic power forces that have shaped vulnerable scenarios in Cartagena. Collaboration between participants and researchers generates conceptual frameworks that make it possible to understand and manage the complexity of HIV's social determination. This way of understanding effectively connects local inequalities with international flows of power such as sexual tourism and makes evident the strengths and limitations of current approaches to HIV prevention.

Human systems dynamics: Toward a computational model

NASA Astrophysics Data System (ADS)

Eoyang, Glenda H.

2012-09-01

A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

Cyclic Game Dynamics Driven by Iterated Reasoning

PubMed Central

Frey, Seth; Goldstone, Robert L.

2013-01-01

Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning–what you think I think you think–will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept. These cycles are driven by a “hopping” behavior that is consistent with other accounts of iterated reasoning: agents are constrained to about two steps of iterated reasoning and learn an additional one-half step with each session. If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems. PMID:23441191

Mean Girls, Homosociality and Football: An Education on Social and Power Dynamics between Girls and Women

ERIC Educational Resources Information Center

Sanders, Kellie

2015-01-01

Relationships between girls and women have typically been explored through the lexicon of "friendship" or, where there is a presence of sexual desire, "lesbian". This article suggests the complexity and impact of female (same-sex) sociality, and its relationship to heteronormativity and power dynamics between girls and women…

A Mathematical Framework for the Complex System Approach to Group Dynamics: The Case of Recovery House Social Integration.

PubMed

Light, John M; Jason, Leonard A; Stevens, Edward B; Callahan, Sarah; Stone, Ariel

2016-03-01

The complex system conception of group social dynamics often involves not only changing individual characteristics, but also changing within-group relationships. Recent advances in stochastic dynamic network modeling allow these interdependencies to be modeled from data. This methodology is discussed within a context of other mathematical and statistical approaches that have been or could be applied to study the temporal evolution of relationships and behaviors within small- to medium-sized groups. An example model is presented, based on a pilot study of five Oxford House recovery homes, sober living environments for individuals following release from acute substance abuse treatment. This model demonstrates how dynamic network modeling can be applied to such systems, examines and discusses several options for pooling, and shows how results are interpreted in line with complex system concepts. Results suggest that this approach (a) is a credible modeling framework for studying group dynamics even with limited data, (b) improves upon the most common alternatives, and (c) is especially well-suited to complex system conceptions. Continuing improvements in stochastic models and associated software may finally lead to mainstream use of these techniques for the study of group dynamics, a shift already occurring in related fields of behavioral science.

Science, Semantics, and Social Change.

ERIC Educational Resources Information Center

Lemke, J. L.

Social semiotics suggests that social and cultural formations, including the language and practice of science and the ways in which new generations and communities advance them, develop as an integral part of the evolution of social ecosystems. Some recent models of complex dynamic systems in physics, chemistry, and biology focus more on the…

Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity.

PubMed

Ramos-Fernandez, Gabriel; King, Andrew J; Beehner, Jacinta C; Bergman, Thore J; Crofoot, Margaret C; Di Fiore, Anthony; Lehmann, Julia; Schaffner, Colleen M; Snyder-Mackler, Noah; Zuberbühler, Klaus; Aureli, Filippo; Boyer, Denis

2018-05-30

Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys ( Ateles geoffroyi ), chimpanzees ( Pan troglodytes ) and geladas ( Theropithecus gelada ). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics. © 2017 The Author(s).

Analyzing the impact of social factors on homelessness: a Fuzzy Cognitive Map approach

PubMed Central

2013-01-01

Background The forces which affect homelessness are complex and often interactive in nature. Social forces such as addictions, family breakdown, and mental illness are compounded by structural forces such as lack of available low-cost housing, poor economic conditions, and insufficient mental health services. Together these factors impact levels of homelessness through their dynamic relations. Historic models, which are static in nature, have only been marginally successful in capturing these relationships. Methods Fuzzy Logic (FL) and fuzzy cognitive maps (FCMs) are particularly suited to the modeling of complex social problems, such as homelessness, due to their inherent ability to model intricate, interactive systems often described in vague conceptual terms and then organize them into a specific, concrete form (i.e., the FCM) which can be readily understood by social scientists and others. Using FL we converted information, taken from recently published, peer reviewed articles, for a select group of factors related to homelessness and then calculated the strength of influence (weights) for pairs of factors. We then used these weighted relationships in a FCM to test the effects of increasing or decreasing individual or groups of factors. Results of these trials were explainable according to current empirical knowledge related to homelessness. Results Prior graphic maps of homelessness have been of limited use due to the dynamic nature of the concepts related to homelessness. The FCM technique captures greater degrees of dynamism and complexity than static models, allowing relevant concepts to be manipulated and interacted. This, in turn, allows for a much more realistic picture of homelessness. Through network analysis of the FCM we determined that Education exerts the greatest force in the model and hence impacts the dynamism and complexity of a social problem such as homelessness. Conclusions The FCM built to model the complex social system of homelessness reasonably represented reality for the sample scenarios created. This confirmed that the model worked and that a search of peer reviewed, academic literature is a reasonable foundation upon which to build the model. Further, it was determined that the direction and strengths of relationships between concepts included in this map are a reasonable approximation of their action in reality. However, dynamic models are not without their limitations and must be acknowledged as inherently exploratory. PMID:23971944

Size does Matter

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

From schools of fish and flocks of birds, to digital networks and self-organizing biopolymers, our understanding of spontaneously emergent phenomena, self-organization, and critical behavior is in large part due to complex systems science. The complex systems approach is indeed a very powerful conceptual framework to shed light on the link between the microscopic dynamical evolution of the basic elements of the system and the emergence of oscopic phenomena; often providing evidence for mathematical principles that go beyond the particulars of the individual system, thus hinting to general modeling principles. By killing the myth of the ant queen and shifting the focus on the dynamical interaction across the elements of the systems, complex systems science has ushered our way into the conceptual understanding of many phenomena at the core of major scientific and social challenges such as the emergence of consensus, social opinion dynamics, conflicts and cooperation, contagion phenomena. For many years though, these complex systems approaches to real-world problems were often suffering from being oversimplified and not grounded on actual data...

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

PubMed

Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G

2014-01-20

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of "biologically basic to socially specific" information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four. Copyright © 2014 Elsevier Ltd. All rights reserved.

The coordination dynamics of social neuromarkers.

PubMed

Tognoli, Emmanuelle; Kelso, J A Scott

2015-01-01

Social behavior is a complex integrative function that entails many aspects of the brain's sensory, cognitive, emotional and movement capacities. Its neural processes are seldom simultaneous but occur according to precise spatiotemporal choreographies, manifested by the coordination of their oscillations within and between brains. Methods with good temporal resolution can help to identify so-called "neuromarkers" of social function and aid in disentangling the dynamical architecture of social brains. In our ongoing research, we have used dual-electroencephalography (EEG) to study neuromarker dynamics during synchronic interactions in which pairs of subjects coordinate behavior spontaneously and intentionally (social coordination) and during diachronic transactions that require subjects to perceive or behave in turn (action observation, delayed imitation). In this paper, after outlining our dynamical approach to the neurophysiological basis of social behavior, we examine commonalities and differences in the neuromarkers that are recruited for both kinds of tasks. We find the neuromarker landscape to be task-specific: synchronic paradigms of social coordination reveal medial mu, alpha and the phi complex as contributing neuromarkers. Diachronic tasks recruit alpha as well, in addition to lateral mu rhythms and the newly discovered nu and kappa rhythms whose functional significance is still unclear. Social coordination, observation, and delayed imitation share commonality of context: in each of our experiments, subjects exchanged information through visual perception and moved in similar ways. Nonetheless, there was little overlap between their neuromarkers, a result that hints strongly of task-specific neural mechanisms for social behavior. The only neuromarker that transcended both synchronic and diachronic social behaviors was the ubiquitous alpha rhythm, which appears to be a key signature of visually-mediated social behaviors. The present paper is both an entry point and a challenge: much work remains to determine the nature and scope of recruitment of other neuromarkers, and to create theoretical models of their within- and between-brain dynamics during social interaction.

The coordination dynamics of social neuromarkers

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2015-01-01

Social behavior is a complex integrative function that entails many aspects of the brain’s sensory, cognitive, emotional and movement capacities. Its neural processes are seldom simultaneous but occur according to precise spatiotemporal choreographies, manifested by the coordination of their oscillations within and between brains. Methods with good temporal resolution can help to identify so-called “neuromarkers” of social function and aid in disentangling the dynamical architecture of social brains. In our ongoing research, we have used dual-electroencephalography (EEG) to study neuromarker dynamics during synchronic interactions in which pairs of subjects coordinate behavior spontaneously and intentionally (social coordination) and during diachronic transactions that require subjects to perceive or behave in turn (action observation, delayed imitation). In this paper, after outlining our dynamical approach to the neurophysiological basis of social behavior, we examine commonalities and differences in the neuromarkers that are recruited for both kinds of tasks. We find the neuromarker landscape to be task-specific: synchronic paradigms of social coordination reveal medial mu, alpha and the phi complex as contributing neuromarkers. Diachronic tasks recruit alpha as well, in addition to lateral mu rhythms and the newly discovered nu and kappa rhythms whose functional significance is still unclear. Social coordination, observation, and delayed imitation share commonality of context: in each of our experiments, subjects exchanged information through visual perception and moved in similar ways. Nonetheless, there was little overlap between their neuromarkers, a result that hints strongly of task-specific neural mechanisms for social behavior. The only neuromarker that transcended both synchronic and diachronic social behaviors was the ubiquitous alpha rhythm, which appears to be a key signature of visually-mediated social behaviors. The present paper is both an entry point and a challenge: much work remains to determine the nature and scope of recruitment of other neuromarkers, and to create theoretical models of their within- and between-brain dynamics during social interaction. PMID:26557067

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Gaze Allocation in a Dynamic Situation: Effects of Social Status and Speaking

ERIC Educational Resources Information Center

Foulsham, Tom; Cheng, Joey T.; Tracy, Jessica L.; Henrich, Joseph; Kingstone, Alan

2010-01-01

Human visual attention operates in a context that is complex, social and dynamic. To explore this, we recorded people taking part in a group decision-making task and then showed video clips of these situations to new participants while tracking their eye movements. Observers spent the majority of time looking at the people in the videos, and in…

Social Insects: A Model System for Network Dynamics

NASA Astrophysics Data System (ADS)

Charbonneau, Daniel; Blonder, Benjamin; Dornhaus, Anna

Social insect colonies (ants, bees, wasps, and termites) show sophisticated collective problem-solving in the face of variable constraints. Individuals exchange information and materials such as food. The resulting network structure and dynamics can inform us about the mechanisms by which the insects achieve particular collective behaviors and these can be transposed to man-made and social networks. We discuss how network analysis can answer important questions about social insects, such as how effective task allocation or information flow is realized. We put forward the idea that network analysis methods are under-utilized in social insect research, and that they can provide novel ways to view the complexity of collective behavior, particularly if network dynamics are taken into account. To illustrate this, we present an example of network tasks performed by ant workers, linked by instances of workers switching from one task to another. We show how temporal network analysis can propose and test new hypotheses on mechanisms of task allocation, and how adding temporal elements to static networks can drastically change results. We discuss the benefits of using social insects as models for complex systems in general. There are multiple opportunities emergent technologies and analysis methods in facilitating research on social insect network. The potential for interdisciplinary work could significantly advance diverse fields such as behavioral ecology, computer sciences, and engineering.

The Social Organization of Schooling

ERIC Educational Resources Information Center

Hedges, Larry V., Ed.; Schneider, Barbara, Ed.

2005-01-01

Schools are complex social settings where students, teachers, administrators, and parents interact to shape a child's educational experience. Any effort to improve educational outcomes for America's children requires a dynamic understanding of the environments in which children learn. In "The Social Organization of Schooling", editors Larry Hedges…

Identifying Developmental Cascades among Differentiated Dimensions of Social Competence and Emotion Regulation

ERIC Educational Resources Information Center

Blair, Bethany L.; Perry, Nicole B.; O'Brien, Marion; Calkins, Susan D.; Keane, Susan P.; Shanahan, Lilly

2015-01-01

This study used data from 356 children, their mothers, teachers, and peers to examine the longitudinal and dynamic associations among 3 dimensions of social competence derived from Hinde's (1987) framework of social complexity: social skills, peer group acceptance, and friendship quality. Direct and indirect associations among each discrete…

Assessing the Dynamic Behavior of Online Q&A Knowledge Markets: A System Dynamics Approach

ERIC Educational Resources Information Center

Jafari, Mostafa; Hesamamiri, Roozbeh; Sadjadi, Jafar; Bourouni, Atieh

2012-01-01

Purpose: The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet-based kind of knowledge market by considering both social and economic interactions. Design/methodology/approach: A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of…

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

PubMed

Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Optimal dimensionality reduction of complex dynamics: The chess game as diffusion on a free-energy landscape

NASA Astrophysics Data System (ADS)

Krivov, Sergei V.

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game—the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

PubMed

Blower, Sally; Go, Myong-Hyun

2011-07-19

Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Young Children's Knowledge About the Moon: A Complex Dynamic System

NASA Astrophysics Data System (ADS)

Venville, Grady J.; Louisell, Robert D.; Wilhelm, Jennifer A.

2012-08-01

The purpose of this research was to use a multidimensional theoretical framework to examine young children's knowledge about the Moon. The research was conducted in the interpretive paradigm and the design was a multiple case study of ten children between the ages of three and eight from the USA and Australia. A detailed, semi-structured interview was conducted with each child. In addition, each child's parents were interviewed to determine possible social and cultural influences on the child's knowledge. We sought evidence about how the social and cultural experiences of the children might have influenced the development of their ideas. From a cognitive perspective we were interested in whether the children's ideas were constructed in a theory like form or whether the knowledge was the result of gradual accumulation of fragments of isolated cultural information. Findings reflected the strong and complex relationship between individual children, their social and cultural milieu, and the way they construct ideas about the Moon and astronomy. Findings are presented around four themes including ontology, creatures and artefacts, animism, and permanence. The findings support a complex dynamic system view of students' knowledge that integrates the framework theory perspective and the knowledge in fragments perspective. An initial model of a complex dynamic system of young children's knowledge about the Moon is presented.

A dynamic social systems model for considering structural factors in HIV prevention and detection

PubMed Central

Latkin, Carl; Weeks, Margaret; Glasman, Laura; Galletly, Carol; Albarracin, Dolores

2010-01-01

We present a model for HIV-related behaviors that emphasizes the dynamic and social nature of the structural factors that influence HIV prevention and detection. Key structural dimensions of the model include resources, science and technology, formal social control, informal social influences and control, social interconnectedness, and settings. These six dimensions can be conceptualized on macro, meso, and micro levels. Given the inherent complexity of structural factors and their interrelatedness, HIV prevention interventions may focus on different levels and dimensions. We employ a systems perspective to describe the interconnected and dynamic processes of change among social systems and their components. The topics of HIV testing and safer injection facilities are analyzed using this structural framework. Finally, we discuss methodological issues in the development and evaluation of structural interventions for HIV prevention and detection. PMID:20838871

Topics in Complexity: Dynamical Patterns in the Cyberworld

NASA Astrophysics Data System (ADS)

Qi, Hong

Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

Being Polish Scientists and Women--between Glorious Past and Difficult Present: The "Reverse Dynamic of Equality Construction"

ERIC Educational Resources Information Center

Wagner, Izabela; Finkielsztein, Mariusz; Czarnacka, Agata

2017-01-01

This paper focuses on the dynamics that animate the situation of women inside academia and the social world of science. Based on a long-term ethnographic study we chose specific cases (scientists educated in Poland) to illustrate the complexity of the career-making process in the 21st century. In this country, in a social and professional…

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Colloquium: Fractional calculus view of complexity: A tutorial

NASA Astrophysics Data System (ADS)

West, Bruce J.

2014-10-01

The fractional calculus has been part of the mathematics and science literature for 310 years. However, it is only in the past decade or so that it has drawn the attention of mainstream science as a way to describe the dynamics of complex phenomena with long-term memory, spatial heterogeneity, along with nonstationary and nonergodic statistics. The most recent application encompasses complex networks, which require new ways of thinking about the world. Part of the new cognition is provided by the fractional calculus description of temporal and topological complexity. Consequently, this Colloquium is not so much a tutorial on the mathematics of the fractional calculus as it is an exploration of how complex phenomena in the physical, social, and life sciences that have eluded traditional mathematical modeling become less mysterious when certain historical assumptions such as differentiability are discarded and the ordinary calculus is replaced with the fractional calculus. Exemplars considered include the fractional differential equations describing the dynamics of viscoelastic materials, turbulence, foraging, and phase transitions in complex social networks.

Impacts of complex behavioral responses on asymmetric interacting spreading dynamics in multiplex networks

PubMed Central

Liu, Quan-Hui; Wang, Wei; Tang, Ming; Zhang, Hai-Feng

2016-01-01

Information diffusion and disease spreading in communication-contact layered network are typically asymmetrically coupled with each other, in which disease spreading can be significantly affected by the way an individual being aware of disease responds to the disease. Many recent studies have demonstrated that human behavioral adoption is a complex and non-Markovian process, where the probability of behavior adoption is dependent on the cumulative times of information received and the social reinforcement effect of the cumulative information. In this paper, the impacts of such a non-Markovian vaccination adoption behavior on the epidemic dynamics and the control effects are explored. It is found that this complex adoption behavior in the communication layer can significantly enhance the epidemic threshold and reduce the final infection rate. By defining the social cost as the total cost of vaccination and treatment, it can be seen that there exists an optimal social reinforcement effect and optimal information transmission rate allowing the minimal social cost. Moreover, a mean-field theory is developed to verify the correctness of simulation results. PMID:27156574

Impacts of complex behavioral responses on asymmetric interacting spreading dynamics in multiplex networks.

PubMed

Liu, Quan-Hui; Wang, Wei; Tang, Ming; Zhang, Hai-Feng

2016-05-09

Information diffusion and disease spreading in communication-contact layered network are typically asymmetrically coupled with each other, in which disease spreading can be significantly affected by the way an individual being aware of disease responds to the disease. Many recent studies have demonstrated that human behavioral adoption is a complex and non-Markovian process, where the probability of behavior adoption is dependent on the cumulative times of information received and the social reinforcement effect of the cumulative information. In this paper, the impacts of such a non-Markovian vaccination adoption behavior on the epidemic dynamics and the control effects are explored. It is found that this complex adoption behavior in the communication layer can significantly enhance the epidemic threshold and reduce the final infection rate. By defining the social cost as the total cost of vaccination and treatment, it can be seen that there exists an optimal social reinforcement effect and optimal information transmission rate allowing the minimal social cost. Moreover, a mean-field theory is developed to verify the correctness of simulation results.

Dynamic properties of epidemic spreading on finite size complex networks

NASA Astrophysics Data System (ADS)

Li, Ying; Liu, Yang; Shan, Xiu-Ming; Ren, Yong; Jiao, Jian; Qiu, Ben

2005-11-01

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS (susceptible-infected-susceptible) model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Topics in Complexity: From Physical to Life Science Systems

NASA Astrophysics Data System (ADS)

Charry, Pedro David Manrique

Complexity seeks to unwrap the mechanisms responsible for collective phenomena across the physical, biological, chemical, economic and social sciences. This thesis investigates real-world complex dynamical systems ranging from the quantum/natural domain to the social domain. The following novel understandings are developed concerning these systems' out-of-equilibrium and nonlinear behavior. Standard quantum techniques show divergent outcomes when a quantum system comprising more than one subunit is far from thermodynamic equilibrium. Abnormal photon inter-arrival times help fulfill the metabolic needs of a terrestrial photosynthetic bacterium. Spatial correlations within incident light can act as a driving mechanism for an organism's adaptation toward more ordered structures. The group dynamics of non-identical objects, whose assembly rules depend on mutual heterogeneity, yield rich transition dynamics between isolation and cohesion, with the cohesion regime reproducing a particular universal pattern commonly found in many real-world systems. Analyses of covert networks reveal collective gender superiority in the connectivity that provides benefits for system robustness and survival. Nodal migration in a network generates complex contagion profiles that lie beyond traditional approaches and yet resemble many modern-day outbreaks.

Natural neural projection dynamics underlying social behavior

PubMed Central

Gunaydin, Lisa A.; Grosenick, Logan; Finkelstein, Joel C.; Kauvar, Isaac V.; Fenno, Lief E.; Adhikari, Avishek; Lammel, Stephan; Mirzabekov, Julie J.; Airan, Raag D.; Zalocusky, Kelly A.; Tye, Kay M.; Anikeeva, Polina; Malenka, Robert C.; Deisseroth, Karl

2014-01-01

Social interaction is a complex behavior essential for many species, and is impaired in major neuropsychiatric disorders. Pharmacological studies have implicated certain neurotransmitter systems in social behavior, but circuit-level understanding of endogenous neural activity during social interaction is lacking. We therefore developed and applied a new methodology, termed fiber photometry, to optically record natural neural activity in genetically- and connectivity-defined projections to elucidate the real-time role of specified pathways in mammalian behavior. Fiber photometry revealed that activity dynamics of a ventral tegmental area (VTA)-to-nucleus accumbens (NAc) projection could encode and predict key features of social but not novel-object interaction. Consistent with this observation, optogenetic control of cells specifically contributing to this projection was sufficient to modulate social behavior, which was mediated by type-1 dopamine receptor signaling downstream in the NAc. Direct observation of projection-specific activity in this way captures a fundamental and previously inaccessible dimension of circuit dynamics. PMID:24949967

Social determinants of health inequalities: towards a theoretical perspective using systems science.

PubMed

Jayasinghe, Saroj

2015-08-25

A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles of systems approach and complexity science (i.e. systems science) to conceptualize social determinants of health inequalities. The conceptualization can be done in two steps: viewing health inequalities from a systems approach and extending it to include complexity science. Systems approach views health inequalities as patterns within the larger rubric of other facets of the human condition, such as educational outcomes and economic development. This anlysis requires more sophisticated models such as systems dynamic models. An extension of the approach is to view systems as complex adaptive systems, i.e. systems that are 'open' and adapt to the environment. They consist of dynamic adapting subsystems that exhibit non-linear interactions, while being 'open' to a similarly dynamic environment of interconnected systems. They exhibit emergent properties that cannot be estimated with precision by using the known interactions among its components (such as economic development, political freedom, health system, culture etc.). Different combinations of the same bundle of factors or determinants give rise to similar patterns or outcomes (i.e. property of convergence), and minor variations in the initial condition could give rise to widely divergent outcomes. Novel approaches using computer simulation models (e.g. agent-based models) would shed light on possible mechanisms as to how factors or determinants interact and lead to emergent patterns of health inequalities of populations.

[Social-professional status, identity, social participation and media utilization. Analysis of a complex dynamics].

PubMed

Laflamme, Simon; Roggero, Pascal; Southcott, Chris

2010-08-01

This article examines the link between the domain and level of occupation, on the one hand, and use of media, including internet, on the other. It adds to this investigation an analysis of identity in its relation to media use and accessibility. It challenges the hypothesis of a strong correlation between level of occupation and use and accessibility to media. It reveals complex phenomena of social homogenization and differentiation. Data is extracted from a sample of workers who completed a questionnaire which focused on use of media.

Threshold behaviors of social dynamics and financial outcomes of Ponzi scheme diffusion in complex networks

NASA Astrophysics Data System (ADS)

Fu, Peihua; Zhu, Anding; Ni, He; Zhao, Xin; Li, Xiulin

2018-01-01

Ponzi schemes always lead to mass disasters after collapse. It is important to study the critical behaviors of both social dynamics and financial outcomes for Ponzi scheme diffusion in complex networks. We develop the potential-investor-divestor-investor (PIDI) model by considering the individual behavior of direct reinvestment. We find that only the spreading rate relates to the epidemic outbreak while the reinvestment rate relates to the zero and non-zero final states for social dynamics of both homo- and inhomogeneous networks. Financially, we find that there is a critical spreading threshold, above which the scheme needs not to use its own initial capital for taking off, i.e. the starting cost is covered by the rapidly inflowing funds. However, the higher the cost per recruit, the larger the critical spreading threshold and the worse the financial outcomes. Theoretical and simulation results also reveal that schemes are easier to take off in inhomogeneous networks. The reinvestment rate does not affect the starting. However, it improves the financial outcome in the early stages and postpones the outbreak of financial collapse. Some policy suggestions for the regulator from the perspective of social physics are proposed in the end of the paper.

The role of future scenarios to understand deep uncertainty

EPA Science Inventory

The environment and its interaction with human systems(economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challe...

Dynamics of organizational culture: Individual beliefs vs. social conformity.

PubMed

Ellinas, Christos; Allan, Neil; Johansson, Anders

2017-01-01

The complex nature of organizational culture challenges our ability to infer its underlying dynamics from observational studies. Recent computational studies have adopted a distinctly different view, where plausible mechanisms are proposed to describe a wide range of social phenomena, including the onset and evolution of organizational culture. In this spirit, this work introduces an empirically-grounded, agent-based model which relaxes a set of assumptions that describes past work-(a) omittance of an individual's strive for achieving cognitive coherence; (b) limited integration of important contextual factors-by utilizing networks of beliefs and incorporating social rank into the dynamics. As a result, we illustrate that: (i) an organization may appear to be increasingly coherent in terms of its organizational culture, yet be composed of individuals with reduced levels of coherence; (ii) the components of social conformity-peer-pressure and social rank-are influential at different aggregation levels.

Dynamics of organizational culture: Individual beliefs vs. social conformity

PubMed Central

Allan, Neil; Johansson, Anders

2017-01-01

The complex nature of organizational culture challenges our ability to infer its underlying dynamics from observational studies. Recent computational studies have adopted a distinctly different view, where plausible mechanisms are proposed to describe a wide range of social phenomena, including the onset and evolution of organizational culture. In this spirit, this work introduces an empirically-grounded, agent-based model which relaxes a set of assumptions that describes past work–(a) omittance of an individual’s strive for achieving cognitive coherence; (b) limited integration of important contextual factors—by utilizing networks of beliefs and incorporating social rank into the dynamics. As a result, we illustrate that: (i) an organization may appear to be increasingly coherent in terms of its organizational culture, yet be composed of individuals with reduced levels of coherence; (ii) the components of social conformity—peer-pressure and social rank—are influential at different aggregation levels. PMID:28665960

Unraveling the complexities of disaster management: a framework for critical social infrastructure to promote population health and resilience.

PubMed

O'Sullivan, Tracey L; Kuziemsky, Craig E; Toal-Sullivan, Darene; Corneil, Wayne

2013-09-01

Complexity is a useful frame of reference for disaster management and understanding population health. An important means to unraveling the complexities of disaster management is to recognize the interdependencies between health care and broader social systems and how they intersect to promote health and resilience before, during and after a crisis. While recent literature has expanded our understanding of the complexity of disasters at the macro level, few studies have examined empirically how dynamic elements of critical social infrastructure at the micro level influence community capacity. The purpose of this study was to explore empirically the complexity of disasters, to determine levers for action where interventions can be used to facilitate collaborative action and promote health among high risk populations. A second purpose was to build a framework for critical social infrastructure and develop a model to identify potential points of intervention to promote population health and resilience. A community-based participatory research design was used in nine focus group consultations (n = 143) held in five communities in Canada, between October 2010 and March 2011, using the Structured Interview Matrix facilitation technique. The findings underscore the importance of interconnectedness of hard and soft systems at the micro level, with culture providing the backdrop for the social fabric of each community. Open coding drawing upon the tenets of complexity theory was used to develop four core themes that provide structure for the framework that evolved; they relate to dynamic context, situational awareness and connectedness, flexible planning, and collaboration, which are needed to foster adaptive responses to disasters. Seven action recommendations are presented, to promote community resilience and population health. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamic social networks based on movement

USGS Publications Warehouse

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

Creating Time: Social Collaboration in Music Improvisation.

PubMed

Walton, Ashley E; Washburn, Auriel; Langland-Hassan, Peter; Chemero, Anthony; Kloos, Heidi; Richardson, Michael J

2018-01-01

Musical collaboration emerges from the complex interaction of environmental and informational constraints, including those of the instruments and the performance context. Music improvisation in particular is more like everyday interaction in that dynamics emerge spontaneously without a rehearsed score or script. We examined how the structure of the musical context affords and shapes interactions between improvising musicians. Six pairs of professional piano players improvised with two different backing tracks while we recorded both the music produced and the movements of their heads, left arms, and right arms. The backing tracks varied in rhythmic and harmonic information, from a chord progression to a continuous drone. Differences in movement coordination and playing behavior were evaluated using the mathematical tools of complex dynamical systems, with the aim of uncovering the multiscale dynamics that characterize musical collaboration. Collectively, the findings indicated that each backing track afforded the emergence of different patterns of coordination with respect to how the musicians played together, how they moved together, as well as their experience collaborating with each other. Additionally, listeners' experiences of the music when rating audio recordings of the improvised performances were related to the way the musicians coordinated both their playing behavior and their bodily movements. Accordingly, the study revealed how complex dynamical systems methods (namely recurrence analysis) can capture the turn-taking dynamics that characterized both the social exchange of the music improvisation and the sounds of collaboration more generally. The study also demonstrated how musical improvisation provides a way of understanding how social interaction emerges from the structure of the behavioral task context. Copyright © 2017 Cognitive Science Society, Inc.

Navigating the Perfect Storm: Research Strategies for Socialecological Systems in a Rapidly Evolving World

NASA Astrophysics Data System (ADS)

Dearing, John A.; Bullock, Seth; Costanza, Robert; Dawson, Terry P.; Edwards, Mary E.; Poppy, Guy M.; Smith, Graham M.

2012-04-01

The `Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.

Dynamical minimalism: why less is more in psychology.

PubMed

Nowak, Andrzej

2004-01-01

The principle of parsimony, embraced in all areas of science, states that simple explanations are preferable to complex explanations in theory construction. Parsimony, however, can necessitate a trade-off with depth and richness in understanding. The approach of dynamical minimalism avoids this trade-off. The goal of this approach is to identify the simplest mechanisms and fewest variables capable of producing the phenomenon in question. A dynamical model in which change is produced by simple rules repetitively interacting with each other can exhibit unexpected and complex properties. It is thus possible to explain complex psychological and social phenomena with very simple models if these models are dynamic. In dynamical minimalist theories, then, the principle of parsimony can be followed without sacrificing depth in understanding. Computer simulations have proven especially useful for investigating the emergent properties of simple models.

Multilevel Dynamic Systems Affecting Introduction of HIV/STI Prevention Innovations among Chinese Women in Sex Work Establishments

ERIC Educational Resources Information Center

Weeks, Margaret R.; Li, Jianghong; Liao, Susu; Zhang, Qingning; Dunn, Jennifer; Wang, Yanhong; Jiang, Jingmei

2013-01-01

Social and public health scientists are increasingly interested in applying system dynamics theory to improve understanding and to harness the forces of change within complex, multilevel systems that affect community intervention implementation, effects, and sustainability. Building a system dynamics model based on ethnographic case study has the…

Land use diversification and intensification on elk winter range in Greater Yellowstone: A framework and agenda for social-ecological research

USGS Publications Warehouse

Haggerty, Julia Hobson; Epstein, Kathleen; Stone, Michael; Cross, Paul

2018-01-01

Amenity migration describes the movement of peoples to rural landscapes and the transition toward tourism and recreation and away from production-oriented land uses (ranching, timber harvesting). The resulting mosaic of land uses and community structures has important consequences for wildlife and their management. This research note examines amenity-driven changes to social-ecological systems in the Greater Yellowstone Ecosystem, specifically in lower elevations that serve as winter habitat for elk. We present a research agenda informed by a preliminary and exploratory mixed-methods investigation: the creation of a “social-impact” index of land use change on elk winter range and a focus group with wildlife management experts. Our findings suggest that elk are encountering an increasingly diverse landscape with respect to land use, while new ownership patterns increase the complexity of social and community dynamics. These factors, in turn, contribute to increasing difficulty meeting wildlife management objectives. To deal with rising complexity across social and ecological landscapes of the Greater Yellowstone Ecosystem, future research will focus on property life cycle dynamics, as well as systems approaches.

The role of future scenarios to understand deep uncertainty in air quality management

EPA Science Inventory

The environment and it’s interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents ...

A natural experiment of social network formation and dynamics.

PubMed

Phan, Tuan Q; Airoldi, Edoardo M

2015-05-26

Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities.

A natural experiment of social network formation and dynamics

PubMed Central

Phan, Tuan Q.; Airoldi, Edoardo M.

2015-01-01

Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities. PMID:25964337

Social complexity beliefs predict posttraumatic growth in survivors of a natural disaster.

PubMed

Nalipay, Ma Jenina N; Bernardo, Allan B I; Mordeno, Imelu G

2016-09-01

Most studies on posttraumatic growth (PTG) have focused on personal characteristics, interpersonal resources, and the immediate environment. There has been less attention on dynamic internal processes related to the development of PTG and on how these processes are affected by the broader culture. Calhoun and Tedeschi's (2006) model suggests a role of distal culture in PTG development, but empirical investigations on that point are limited. The present study investigated the role of social complexity-the generalized belief about changing social environments and inconsistency of human behavior-as a predictor of PTG. Social complexity was hypothesized to be associated with problem-solving approaches that are likely to give rise to cognitive processes that promote PTG. A sample of 446 survivors of Typhoon Haiyan, 1 of the strongest typhoons ever recorded at the time, answered self-report measures of social complexity, cognitive processing of trauma, and PTG. Structural equation modeling indicated a good fit between the data and the hypothesized model; belief in social complexity predicted stronger PTG, mediated by cognitive processing. The results provide evidence for how disaster survivors' beliefs about the changing nature of social environments and their corresponding behavior changes are predictors of PTG and suggest a psychological mechanism for how distal culture can influence PTG. Thus, assessing social complexity beliefs during early the phases of a postdisaster psychosocial intervention may provide useful information on who is likely to experience PTG. Trauma workers might consider culture-specific social themes related to social complexity in disaster-affected communities. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Emergence of communities and diversity in social networks

PubMed Central

Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross

2017-01-01

Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics. PMID:28235785

Emergence of communities and diversity in social networks.

PubMed

Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross; Stanley, H Eugene

2017-03-14

Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.

Modeling Social Capital as Dynamic Networks to Promote Access to Oral Healthcare

PubMed Central

Northridge, Mary E.; Kunzel, Carol; Zhang, Qiuyi; Kum, Susan S.; Gilbert, Jessica L.; Jin, Zhu; Metcalf, Sara S.

2016-01-01

Social capital, as comprised of human connections in social networks and their associated benefits, is closely related to the health of individuals, communities, and societies at large. For disadvantaged population groups such as older adults and racial/ethnic minorities, social capital may play a particularly critical role in mitigating the negative effects and reinforcing the positive effects on health. In this project, we model social capital as both cause and effect by simulating dynamic networks. Informed in part by a community-based health promotion program, an agent-based model is contextualized in a GIS environment to explore the complexity of social disparities in oral and general health as experienced at the individual, interpersonal, and community scales. This study provides the foundation for future work investigating how health and healthcare accessibility may be influenced by social networks. PMID:27668298

Modeling Social Capital as Dynamic Networks to Promote Access to Oral Healthcare.

PubMed

Wang, Hua; Northridge, Mary E; Kunzel, Carol; Zhang, Qiuyi; Kum, Susan S; Gilbert, Jessica L; Jin, Zhu; Metcalf, Sara S

2016-01-01

Social capital, as comprised of human connections in social networks and their associated benefits, is closely related to the health of individuals, communities, and societies at large. For disadvantaged population groups such as older adults and racial/ethnic minorities, social capital may play a particularly critical role in mitigating the negative effects and reinforcing the positive effects on health. In this project, we model social capital as both cause and effect by simulating dynamic networks. Informed in part by a community-based health promotion program, an agent-based model is contextualized in a GIS environment to explore the complexity of social disparities in oral and general health as experienced at the individual, interpersonal, and community scales. This study provides the foundation for future work investigating how health and healthcare accessibility may be influenced by social networks.

Using Social Network Graphs as Visualization Tools to Influence Peer Selection Decision-Making Strategies to Access Information about Complex Socioscientific Issues

ERIC Educational Resources Information Center

Yoon, Susan A.

2011-01-01

This study extends previous research that explores how visualization affordances that computational tools provide and social network analyses that account for individual- and group-level dynamic processes can work in conjunction to improve learning outcomes. The study's main hypothesis is that when social network graphs are used in instruction,…

The Influence of Presentation Modality on the Social Comprehension of Naturalistic Scenes in Adults with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Gedek, Haley M.; Pantelis, Peter C.; Kennedy, Daniel P.

2018-01-01

The comprehension of dynamically unfolding social situations is made possible by the seamless integration of multimodal information merged with rich intuitions about the thoughts and behaviors of others. We examined how high-functioning adults with autism spectrum disorder and neurotypical controls made a complex social judgment (i.e. rating the…

Complex Dynamics in Information Sharing Networks

NASA Astrophysics Data System (ADS)

Cronin, Bruce

This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

Emergence of hysteresis loop in social contagions on complex networks.

PubMed

Su, Zhen; Wang, Wei; Li, Lixiang; Xiao, Jinghua; Stanley, H Eugene

2017-07-21

Understanding the spreading mechanisms of social contagions in complex network systems has attracted much attention in the physics community. Here we propose a generalized threshold model to describe social contagions. Using extensive numerical simulations and theoretical analyses, we find that a hysteresis loop emerges in the system. Specifically, the steady state of the system is sensitive to the initial conditions of the dynamics of the system. In the steady state, the adoption size increases discontinuously with the transmission probability of information about social contagions, and trial size exhibits a non-monotonic pattern, i.e., it first increases discontinuously then decreases continuously. Finally we study social contagions on heterogeneous networks and find that network topology does not qualitatively affect our results.

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

NASA Astrophysics Data System (ADS)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

Beyond the checklist: understanding rural health vulnerability in a South African context.

PubMed

Vergunst, Richard; Swartz, Leslie; Mji, Gubela; Kritzinger, Janis; Braathen, Stine Hellum

2016-01-01

Vulnerability in the past has sometimes been measured and understood in terms of checklists or common understanding. It is argued here that vulnerability is a more complex issue than this. Although checklists of vulnerable groups are important, they do not capture the essence and dynamics of vulnerability. The case of rural health vulnerability in South Africa is discussed to show that classifying people into vulnerable groups does not portray the complexity and intricacies of what it means to have vulnerability. We also wish to show that there are different kinds of vulnerabilities, and the difference between access vulnerability and illness vulnerability is highlighted. As part of a larger study, this case study is presented to show how vulnerability in a poor rural community in South Africa has to be understood in a contextual and dynamic manner as opposed to a static manner. Family and social dynamics can influence health. For example, fractured families were seen as a vulnerable issue within the community, while being a person with a disability can lead to isolation and callous attitudes towards them. It is these family and social dynamics that lead proximally to vulnerability to ill health. A contextual approach can assist in giving a more layered understanding of vulnerability than a checklist approach can do. Interventions to change health cannot be addressed simply by medical means. Social conditions need to be changed, and part of changing social conditions is the process of assisting those who are isolated or experience themselves as vulnerable to reconnect with others in the community. Poverty leads to social exclusion; social and family inclusion may be key to well-being.

Towards understanding the dynamic behaviour of floodplains as human-water systems

NASA Astrophysics Data System (ADS)

Di Baldassarre, G.; Kooy, M.; Kemerink, J. S.; Brandimarte, L.

2013-03-01

This paper offers a conceptual approach to explore the complex dynamics of floodplains as fully coupled human-water systems. A number of hydrologists have recently investigated the impact of human activities (such as flood control measures, land-use changes, and settlement patterns) on the frequency and severity of floods. Meanwhile, social scientists have shown how interactions between society and waters in floodplain areas, including the frequency and severity of floods, have an impact on the ways in which social relations unfold (in terms of governance processes, policies, and institutions) and societies are organised (spatially, politically, and socially). However, we argue that the interactions and associated feedback mechanisms between hydrological and social processes remain largely unexplored and poorly understood. Thus, there is a need to better understand how the institutions and governance processes interact with hydrological processes in floodplains to influence the frequency and severity of floods, while (in turn) hydrological processes co-constitute the social realm and make a difference for how social relations unfold to shape governance processes and institutions. Our research goal, therefore, is not in identifying one or the other side of the cycle (hydrological or social), but in explaining the relationship between them: how, when, where, and why they interact, and to what result for both social relations and hydrological processes? We argue that long time series of hydrological and social data, along with remote sensing data, can be used to observe floodplain dynamics from unconventional approaches, and understand the complex interactions between water and human systems taking place in floodplain areas, across scales and levels of human impacts, and within different hydro-climatic conditions, socio-cultural settings, and modes of governance.

Towards understanding the dynamic behaviour of floodplains as human-water systems

NASA Astrophysics Data System (ADS)

Di Baldassarre, G.; Kooy, M.; Kemerink, J. S.; Brandimarte, L.

2013-08-01

This paper offers a conceptual approach to explore the complex dynamics of floodplains as fully coupled human-water systems. A number of hydrologists have recently investigated the impact of human activities (such as flood control measures, land-use changes, and settlement patterns) on the frequency and severity of floods. Meanwhile, social scientists have shown how interactions between society and waters in deltas and floodplain areas, including the frequency and severity of floods, have an impact on the ways in which social relations unfold (in terms of governance processes, policies, and institutions) and societies are organised (spatially, politically, and socially). However, we argue that the interactions and associated feedback mechanisms between hydrological and social processes remain largely unexplored and poorly understood. Thus, there is a need to better understand how the institutions and governance processes interact with hydrological processes in deltas and floodplains to influence the frequency and severity of floods, while (in turn) hydrological processes co-constitute the social realm and make a difference for how social relations unfold to shape governance processes and institutions. Our research goal, therefore, is not in identifying one or the other side of the cycle (hydrological or social), but in explaining the relationship between them: how, when, where, and why they interact, and to what result for both social relations and hydrological processes? We argue that long time series of hydrological and social data, along with remote sensing data, can be used to observe floodplain dynamics from unconventional approaches, and understand the complex interactions between water and human systems taking place in floodplain areas, across scales and levels of human impacts, and within different hydro-climatic conditions, socio-cultural settings, and modes of governance.

Live Theatre: A Dynamic Medium for Engaging with Intercultural Education Research

ERIC Educational Resources Information Center

Nelson, Cynthia D.

2013-01-01

In this paper, I discuss live theatre as a highly effective and dynamic medium for facilitating meaningful engagement with research on intercultural education. I make the case that ethnographic, or research-based, theatre can productively showcase challenging social issues and the sometimes confusing, poignant and humorous complexities of…

Immediate early gene activation throughout the brain is associated with dynamic changes in social context.

PubMed

Williamson, Cait M; Klein, Inbal S; Lee, Won; Curley, James P

2018-05-31

Social competence is dependent on successful processing of social context information. The social opportunity paradigm is a methodology in which dynamic shifts in social context are induced through removal of the alpha male in a dominance hierarchy, leading to rapid ascent in the hierarchy of the beta male and of other subordinate males in the social group. In the current study, we use the social opportunity paradigm to determine what brain regions respond to this dynamic change in social context, allowing an individual to recognize the absence of the alpha male and subsequently perform status-appropriate social behaviors. Replicating our previous work, we show that following removal of the alpha male, beta males rapidly ascend the social hierarchy and attain dominant status by increasing aggression towards more subordinate individuals. Analysis of patterns of Fos immunoreactivity throughout the brain indicates that in individuals undergoing social ascent, there is increased activity in regions of the social behavior network, as well as the infralimbic and prelimbic regions of the prefrontal cortex and areas of the hippocampus. Our findings demonstrate that male mice are able to respond to changes in social context and provide insight into the how the brain processes these complex behavioral changes.

Multi-stage complex contagions.

PubMed

Melnik, Sergey; Ward, Jonathan A; Gleeson, James P; Porter, Mason A

2013-03-01

The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages-which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea-exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades-and hence collective action-can be driven not only by high-stage influencers but also by low-stage influencers.

Multi-stage complex contagions

NASA Astrophysics Data System (ADS)

Melnik, Sergey; Ward, Jonathan A.; Gleeson, James P.; Porter, Mason A.

2013-03-01

The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages—which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea—exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades—and hence collective action—can be driven not only by high-stage influencers but also by low-stage influencers.

Reciprocity, Punishment, Institutions: The Streets to Social Collaboration -- New Theories on How Emerging Social Artifacts Control Our Lives in Society

NASA Astrophysics Data System (ADS)

Gerace, Giuliana

What mechanisms induce and support cooperation in social interaction? Traditional rational-choice perspective has resulted ineffective to keep track of complex real-world dynamics of cooperation. On the other hand, perspectives based on the justification of fairness preferences as internalized behavioural forces driving realistic cooperative interactions are notoriously incomplete and rather fuzzy with respect to their theoretical foundations. After considering recognized evolutionary accounts of the emergence and resilience of social standards, we endorse the view according to which the key to understanding evolutionary dynamics of social engagement is to be found in individual motivational attitudes to interaction. But, beyond any psychological implications, we suggest not exiting from the "logic of reciprocity" in considering the rationality of preferences for social interaction. Preliminary supporting experimental evidence is provided.

The simple rules of social contagion.

PubMed

Hodas, Nathan O; Lerman, Kristina

2014-03-11

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

The Simple Rules of Social Contagion

NASA Astrophysics Data System (ADS)

Hodas, Nathan O.; Lerman, Kristina

2014-03-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

Social and strategic imitation: the way to consensus.

PubMed

Vilone, Daniele; Ramasco, José J; Sánchez, Angel; Miguel, Maxi San

2012-01-01

Humans do not always make rational choices, a fact that experimental economics is putting on solid grounds. The social context plays an important role in determining our actions, and often we imitate friends or acquaintances without any strategic consideration. We explore here the interplay between strategic and social imitative behavior in a coordination problem on a social network. We observe that for interactions on 1D and 2D lattices any amount of social imitation prevents the freezing of the network in domains with different conventions, thus leading to global consensus. For interactions on complex networks, the interplay of social and strategic imitation also drives the system towards global consensus while neither dynamics alone does. We find an optimum value for the combination of imitative behaviors to reach consensus in a minimum time, and two different dynamical regimes to approach it: exponential when social imitation predominates, power-law when strategic considerations prevail.

From Complex to Simple: Interdisciplinary Stochastic Models

ERIC Educational Resources Information Center

Mazilu, D. A.; Zamora, G.; Mazilu, I.

2012-01-01

We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions…

Developmental Evaluation: Applying Complexity Concepts to Enhance Innovation and Use

ERIC Educational Resources Information Center

Patton, Michael Quinn

2010-01-01

Developmental evaluation (DE) offers a powerful approach to monitoring and supporting social innovations by working in partnership with program decision makers. In this book, eminent authority shows how to conduct evaluations within a DE framework. Patton draws on insights about complex dynamic systems, uncertainty, nonlinearity, and emergence. He…

The Speech Community in Evolutionary Language Dynamics

ERIC Educational Resources Information Center

Blythe, Richard A.; Croft, William A.

2009-01-01

Language is a complex adaptive system: Speakers are agents who interact with each other, and their past and current interactions feed into speakers' future behavior in complex ways. In this article, we describe the social cognitive linguistic basis for this analysis of language and a mathematical model developed in collaboration between…

Modeling social crowds. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Poyato, David; Soler, Juan

2016-09-01

The study of human behavior is a complex task, but modeling some aspects of this behavior is an even more complicated and exciting idea. From crisis management to decision making in evacuation protocols, understanding the complexity of humans in stress situations is more and more demanded in our society by obvious reasons [5,6,8,12]. In this context, [4] deals with crowd dynamics with special attention to evacuation.

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

Individual differences in the spontaneous recruitment of brain regions supporting mental state understanding when viewing natural social scenes.

PubMed

Wagner, Dylan D; Kelley, William M; Heatherton, Todd F

2011-12-01

People are able to rapidly infer complex personality traits and mental states even from the most minimal person information. Research has shown that when observers view a natural scene containing people, they spend a disproportionate amount of their time looking at the social features (e.g., faces, bodies). Does this preference for social features merely reflect the biological salience of these features or are observers spontaneously attempting to make sense of complex social dynamics? Using functional neuroimaging, we investigated neural responses to social and nonsocial visual scenes in a large sample of participants (n = 48) who varied on an individual difference measure assessing empathy and mentalizing (i.e., empathizing). Compared with other scene categories, viewing natural social scenes activated regions associated with social cognition (e.g., dorsomedial prefrontal cortex and temporal poles). Moreover, activity in these regions during social scene viewing was strongly correlated with individual differences in empathizing. These findings offer neural evidence that observers spontaneously engage in social cognition when viewing complex social material but that the degree to which people do so is mediated by individual differences in trait empathizing.

Mouse Social Network Dynamics and Community Structure are Associated with Plasticity-Related Brain Gene Expression

PubMed Central

Williamson, Cait M.; Franks, Becca; Curley, James P.

2016-01-01

Laboratory studies of social behavior have typically focused on dyadic interactions occurring within a limited spatiotemporal context. However, this strategy prevents analyses of the dynamics of group social behavior and constrains identification of the biological pathways mediating individual differences in behavior. In the current study, we aimed to identify the spatiotemporal dynamics and hierarchical organization of a large social network of male mice. We also sought to determine if standard assays of social and exploratory behavior are predictive of social behavior in this social network and whether individual network position was associated with the mRNA expression of two plasticity-related genes, DNA methyltransferase 1 and 3a. Mice were observed to form a hierarchically organized social network and self-organized into two separate social network communities. Members of both communities exhibited distinct patterns of socio-spatial organization within the vivaria that was not limited to only agonistic interactions. We further established that exploratory and social behaviors in standard behavioral assays conducted prior to placing the mice into the large group was predictive of initial network position and behavior but were not associated with final social network position. Finally, we determined that social network position is associated with variation in mRNA levels of two neural plasticity genes, DNMT1 and DNMT3a, in the hippocampus but not the mPOA. This work demonstrates the importance of understanding the role of social context and complex social dynamics in determining the relationship between individual differences in social behavior and brain gene expression. PMID:27540359

Multiple time-scales and the developmental dynamics of social systems

PubMed Central

Flack, Jessica C.

2012-01-01

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the ‘coarseness’ of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. PMID:22641819

Multiple time-scales and the developmental dynamics of social systems.

PubMed

Flack, Jessica C

2012-07-05

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.

Social-ecological dynamics of change and restoration attempts in the Chihuahuan Desert grasslands of Janos Biosphere Reserve, Mexico

USDA-ARS?s Scientific Manuscript database

Shrub encroachment and grassland loss are widespread throughout the US-Mexico borderlands with negative consequences for production of livestock and ecosystem services. In this paper we detail the complex social and ecological phenomena associated with this pattern of degradation in a large area in ...

Controlling collective dynamics in complex minority-game resource-allocation systems

NASA Astrophysics Data System (ADS)

Zhang, Ji-Qiang; Huang, Zi-Gang; Dong, Jia-Qi; Huang, Liang; Lai, Ying-Cheng

2013-05-01

Resource allocation takes place in various kinds of real-world complex systems, such as traffic systems, social services institutions or organizations, or even ecosystems. The fundamental principle underlying complex resource-allocation dynamics is Boolean interactions associated with minority games, as resources are generally limited and agents tend to choose the least used resource based on available information. A common but harmful dynamical behavior in resource-allocation systems is herding, where there are time intervals during which a large majority of the agents compete for a few resources, leaving many other resources unused. Accompanying the herd behavior is thus strong fluctuations with time in the number of resources being used. In this paper, we articulate and establish that an intuitive control strategy, namely pinning control, is effective at harnessing the herding dynamics. In particular, by fixing the choices of resources for a few agents while leaving the majority of the agents free, herding can be eliminated completely. Our investigation is systematic in that we consider random and targeted pinning and a variety of network topologies, and we carry out a comprehensive analysis in the framework of mean-field theory to understand the working of control. The basic philosophy is then that, when a few agents waive their freedom to choose resources by receiving sufficient incentives, the majority of the agents benefit in that they will make fair, efficient, and effective use of the available resources. Our work represents a basic and general framework to address the fundamental issue of fluctuations in complex dynamical systems with significant applications to social, economical, and political systems.

SOCR "Motion Charts": An Efficient, Open-Source, Interactive and Dynamic Applet for Visualizing Longitudinal Multivariate Data

ERIC Educational Resources Information Center

Al-Aziz, Jameel; Christou, Nicolas; Dinov, Ivo D.

2010-01-01

The amount, complexity and provenance of data have dramatically increased in the past five years. Visualization of observed and simulated data is a critical component of any social, environmental, biomedical or scientific quest. Dynamic, exploratory and interactive visualization of multivariate data, without preprocessing by dimensionality…

A Complex Dynamic Systems Perspective on Identity and Its Development: The Dynamic Systems Model of Role Identity

ERIC Educational Resources Information Center

Kaplan, Avi; Garner, Joanna K.

2017-01-01

Current prominent models of identity face challenges in bridging across divergent perspectives and apparent dichotomies such as personal or social-collective, conscious or unconscious, and epigenetic or discursive-relational, and affording pursuit of research questions that allows integrative answers. This article presents a coherent theoretical…

Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

NASA Astrophysics Data System (ADS)

Ward, Jonathan A.; Grindrod, Peter

2014-07-01

Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance here, cultural dissemination [47,12,48].Combining the effects of social influence and homophily naturally gives rise to an adaptive network, since social influence causes the states of agents that are strongly connected to become more similar, while homophily strengthens connections between agents whose states are already similar.1

The dual impact of ecology and management on social incentives in marine common-pool resource systems.

PubMed

Klein, E S; Barbier, M R; Watson, J R

2017-08-01

Understanding how and when cooperative human behaviour forms in common-pool resource systems is critical to illuminating social-ecological systems and designing governance institutions that promote sustainable resource use. Before assessing the full complexity of social dynamics, it is essential to understand, concretely and mechanistically, how resource dynamics and human actions interact to create incentives and pay-offs for social behaviours. Here, we investigated how such incentives for information sharing are affected by spatial dynamics and management in a common-pool resource system. Using interviews with fishermen to inform an agent-based model, we reveal generic mechanisms through which, for a given ecological setting characterized by the spatial dynamics of the resource, the two 'human factors' of information sharing and management may heterogeneously impact various members of a group for whom theory would otherwise predict the same strategy. When users can deplete the resource, these interactions are further affected by the management approach. Finally, we discuss the implications of alternative motivations, such as equity among fishermen and consistency of the fleet's output. Our results indicate that resource spatial dynamics, form of management and level of depletion can interact to alter the sociality of people in common-pool resource systems, providing necessary insight for future study of strategic decision processes.

Modelling opinion formation driven communities in social networks

NASA Astrophysics Data System (ADS)

Iñiguez, Gerardo; Barrio, Rafael A.; Kertész, János; Kaski, Kimmo K.

2011-09-01

In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter α, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realised by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter α and its influence on the conformation of opinion and the size of the resulting communities. We present numerical studies and extract interesting features of the model that can be interpreted in terms of social behaviour.

Social influence and bullying behavior: intervention-based network dynamics of the fairplayer.manual bullying prevention program.

PubMed

Wölfer, Ralf; Scheithauer, Herbert

2014-01-01

Bullying is a social phenomenon and although preventive interventions consequently address social mechanisms, evaluations hardly consider the complexity of peer processes. Therefore, the present study analyzes the efficacy of the fairplayer.manual bullying prevention program from a social network perspective. Within a pretest-posttest control group design, longitudinal data were available from 328 middle-school students (MAge  = 13.7 years; 51% girls), who provided information on bullying behavior and interaction patterns. The revealed network parameters were utilized to examine the network change (MANCOVA) and the network dynamics (SIENA). Across both forms of analyses, findings revealed the hypothesized intervention-based decrease of bullies' social influence. Hence the present bullying prevention program, as one example of programs that successfully addresses both individual skills and social mechanisms, demonstrates the desired effect of reducing contextual opportunities for the exhibition of bullying behavior. © 2014 Wiley Periodicals, Inc.

The Simple Rules of Social Contagion

PubMed Central

Hodas, Nathan O.; Lerman, Kristina

2014-01-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior. PMID:24614301

Dynamic model of time-dependent complex networks.

PubMed

Hill, Scott A; Braha, Dan

2010-10-01

The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by irregular connections that evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present an approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme.

Density dependence in group dynamics of a highly social mongoose, Suricata suricatta.

PubMed

Bateman, Andrew W; Ozgul, Arpat; Coulson, Tim; Clutton-Brock, Tim H

2012-05-01

1. For social species, the link between individual behaviour and population dynamics is mediated by group-level demography. 2. Populations of obligate cooperative breeders are structured into social groups, which may be subject to inverse density dependence (Allee effects) that result from a dependence on conspecific helpers, but evidence for population-wide Allee effects is rare. 3. We use field data from a long-term study of cooperative meerkats (Suricata suricatta; Schreber, 1776) - a species for which local Allee effects are not reflected in population-level dynamics - to empirically model interannual group dynamics. 4. Using phenomenological population models, modified to incorporate environmental conditions and potential Allee effects, we first investigate overall patterns of group dynamics and find support only for conventional density dependence that increases after years of low rainfall. 5. To explain the observed patterns, we examine specific demographic rates and assess their contributions to overall group dynamics. Although per-capita meerkat mortality is subject to a component Allee effect, it contributes relatively little to observed variation in group dynamics, and other (conventionally density dependent) demographic rates - especially emigration - govern group dynamics. 6. Our findings highlight the need to consider demographic processes and density dependence in subpopulations before drawing conclusions about how behaviour affects population processes in socially complex systems. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.

Conceptual shifts needed to understand the dynamic interactions of genes, environment, epigenetics, social processes, and behavioral choices.

PubMed

Jackson, Fatimah L C; Niculescu, Mihai D; Jackson, Robert T

2013-10-01

Social and behavioral research in public health is often intimately tied to profound, but frequently neglected, biological influences from underlying genetic, environmental, and epigenetic events. The dynamic interplay between the life, social, and behavioral sciences often remains underappreciated and underutilized in addressing complex diseases and disorders and in developing effective remediation strategies. Using a case-study format, we present examples as to how the inclusion of genetic, environmental, and epigenetic data can augment social and behavioral health research by expanding the parameters of such studies, adding specificity to phenotypic assessments, and providing additional internal control in comparative studies. We highlight the important roles of gene-environment interactions and epigenetics as sources of phenotypic change and as a bridge between the life and social and behavioral sciences in the development of robust interdisciplinary analyses.

Dynamic calibration of agent-based models using data assimilation.

PubMed

Ward, Jonathan A; Evans, Andrew J; Malleson, Nicolas S

2016-04-01

A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

Complex contagion process in spreading of online innovation

PubMed Central

Karsai, Márton; Iñiguez, Gerardo; Kaski, Kimmo; Kertész, János

2014-01-01

Diffusion of innovation can be interpreted as a social spreading phenomenon governed by the impact of media and social interactions. Although these mechanisms have been identified by quantitative theories, their role and relative importance are not entirely understood, as empirical verification has so far been hindered by the lack of appropriate data. Here we analyse a dataset recording the spreading dynamics of the world's largest Voice over Internet Protocol service to empirically support the assumptions behind models of social contagion. We show that the rate of spontaneous service adoption is constant, the probability of adoption via social influence is linearly proportional to the fraction of adopting neighbours, and the rate of service termination is time-invariant and independent of the behaviour of peers. By implementing the detected diffusion mechanisms into a dynamical agent-based model, we are able to emulate the adoption dynamics of the service in several countries worldwide. This approach enables us to make medium-term predictions of service adoption and disclose dependencies between the dynamics of innovation spreading and the socio-economic development of a country. PMID:25339685

Inductive Game Theory and the Dynamics of Animal Conflict

PubMed Central

DeDeo, Simon; Krakauer, David C.; Flack, Jessica C.

2010-01-01

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management. PMID:20485557

Inductive game theory and the dynamics of animal conflict.

PubMed

DeDeo, Simon; Krakauer, David C; Flack, Jessica C

2010-05-13

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in an monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management.

Aging, memory, and nonhierarchical energy landscape of spin jam

NASA Astrophysics Data System (ADS)

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-10-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes.

Multiple scales modelling approaches to social interaction in crowd dynamics and crisis management. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Trucu, Dumitru

2016-09-01

In this comprehensive review concerning the modelling of human behaviours in crowd dynamics [3], the authors explore a wide range of mathematical approaches spanning over multiple scales that are suitable to describe emerging crowd behaviours in extreme situations. Focused on deciphering the key aspects leading to emerging crowd patterns evolutions in challenging times such as those requiring an evacuation on a complex venue, the authors address this complex dynamics at both microscale (individual level), mesoscale (probability distributions of interacting individuals), and macroscale (population level), ultimately aiming to gain valuable understanding and knowledge that would inform decision making in managing crisis situations.

Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion.

PubMed

Baggio, Jacopo A; BurnSilver, Shauna B; Arenas, Alex; Magdanz, James S; Kofinas, Gary P; De Domenico, Manlio

2016-11-29

Network analysis provides a powerful tool to analyze complex influences of social and ecological structures on community and household dynamics. Most network studies of social-ecological systems use simple, undirected, unweighted networks. We analyze multiplex, directed, and weighted networks of subsistence food flows collected in three small indigenous communities in Arctic Alaska potentially facing substantial economic and ecological changes. Our analysis of plausible future scenarios suggests that changes to social relations and key households have greater effects on community robustness than changes to specific wild food resources.

Unravelling the Social Dynamics of an Industry-School Partnership: Social Capital as Perspective for Co-Creation

ERIC Educational Resources Information Center

Ehlen, Corry G. J. M.; van der Klink, Marcel R.; Boshuizen, Henny P. A.

2016-01-01

Increasingly, innovative collaboration between industry and schools is being exploited as a way of improving the quality and relevance of education. Even though these innovations appear to have substantial benefits, often the impact proves to fade away after their implementation. A better understanding of how to sustain complex innovations seems…

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

A coevolving model based on preferential triadic closure for social media networks

PubMed Central

Li, Menghui; Zou, Hailin; Guan, Shuguang; Gong, Xiaofeng; Li, Kun; Di, Zengru; Lai, Choy-Heng

2013-01-01

The dynamical origin of complex networks, i.e., the underlying principles governing network evolution, is a crucial issue in network study. In this paper, by carrying out analysis to the temporal data of Flickr and Epinions–two typical social media networks, we found that the dynamical pattern in neighborhood, especially the formation of triadic links, plays a dominant role in the evolution of networks. We thus proposed a coevolving dynamical model for such networks, in which the evolution is only driven by the local dynamics–the preferential triadic closure. Numerical experiments verified that the model can reproduce global properties which are qualitatively consistent with the empirical observations. PMID:23979061

Understanding the Online Informal Learning of English as a Complex Dynamic System: An Emic Approach

ERIC Educational Resources Information Center

Sockett, Geoffrey

2013-01-01

Research into the online informal learning of English has already shown it to be a widespread phenomenon involving a range of comprehension and production activities such as viewing original version television series, listening to music on demand and social networking with other English users. Dynamic systems theory provides a suitable framework…

Nonlinear Dynamics on Interconnected Networks

NASA Astrophysics Data System (ADS)

Arenas, Alex; De Domenico, Manlio

2016-06-01

Networks of dynamical interacting units can represent many complex systems, from the human brain to transportation systems and societies. The study of these complex networks, when accounting for different types of interactions has become a subject of interest in the last few years, especially because its representational power in the description of users' interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.) [1], or in representing different transportation modes in urban networks [2,3]. The general name coined for these networks is multilayer networks, where each layer accounts for a type of interaction (see Fig. 1).

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

Making Sense of How Physician Preceptors Interact with Medical Students: Discourses of Dialogue, Good Medical Practice, and Relationship Trajectories

ERIC Educational Resources Information Center

van der Zwet, J.; Dornan, T.; Teunissen, P. W.; de Jonge, L. P. J. W. M.; Scherpbier, A. J. J. A.

2014-01-01

Work based learning and teaching in health care settings are complex and dynamic. Sociocultural theory addresses this complexity by focusing on interaction between learners, teachers, and their environment as learners develop their professional identity. Although social interaction between doctors and students plays a crucial role in this…

Understanding Islamist political violence through computational social simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watkins, Jennifer H; Mackerrow, Edward P; Patelli, Paolo G

Understanding the process that enables political violence is of great value in reducing the future demand for and support of violent opposition groups. Methods are needed that allow alternative scenarios and counterfactuals to be scientifically researched. Computational social simulation shows promise in developing 'computer experiments' that would be unfeasible or unethical in the real world. Additionally, the process of modeling and simulation reveals and challenges assumptions that may not be noted in theories, exposes areas where data is not available, and provides a rigorous, repeatable, and transparent framework for analyzing the complex dynamics of political violence. This paper demonstrates themore » computational modeling process using two simulation techniques: system dynamics and agent-based modeling. The benefits and drawbacks of both techniques are discussed. In developing these social simulations, we discovered that the social science concepts and theories needed to accurately simulate the associated psychological and social phenomena were lacking.« less

Integrating research tools to support the management of social-ecological systems under climate change

USGS Publications Warehouse

Miller, Brian W.; Morisette, Jeffrey T.

2014-01-01

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Rat pup social motivation: A critical component of early psychological development

PubMed Central

Cromwell, Howard Casey

2011-01-01

Examining the role of the offspring in early social dynamics is especially difficult. Human developmental psychology has found infant behavior to be a vital part of the early environmental setting. In the rodent model, the different ways that a rodent neonate or pup can influence social dynamics are not well known. Typically, litters of neonates or pups offer complex social interactions dominated by behavior seemingly initiated and maintained by the primary caregiver (e.g., the dam). Despite this strong role for the caregiver, the young most likely influence the litter dynamics in many powerful ways including communication signals, discrimination abilities and early approach behavior. Nelson and Panksepp (1996) developed a preference task to examine early rodent pup social motivation. We have used the same task to examine how variations in maternal care or different environmental perturbations could alter the rat pup preferences for social-related stimuli. Rat pups receiving low levels of maternal licking and grooming were impaired in maternal odor cue learning and emitted lower levels of 22 kHz ultrasounds compared to pups from the high licking and grooming cohort. Prenatal stress or early exposure to a toxicant (polychlorinated biphenyl) altered early social preferences in the rat pup in different ways indicating that diverse strategies are expressed and specific to the type of perturbation exposure. A greater focus on the offspring motivation following early ‘stressors’ will allow for more complete understanding of the dynamics in behavior during early social development. PMID:21251926

Understanding the dynamics of sustainable change: A 20-year case study of integrated health and social care.

PubMed

Klinga, Charlotte; Hasson, Henna; Andreen Sachs, Magna; Hansson, Johan

2018-06-04

Change initiatives face many challenges, and only a few lead to long-term sustainability. One area in which the challenge of achieving long-term sustainability is particularly noticeable is integrated health and social care. Service integration is crucial for a wide range of patients including people with complex mental health and social care needs. However, previous research has focused on the initiation, resistance and implementation of change, while longitudinal studies remain sparse. The objective of this study was therefore to gain insight into the dynamics of sustainable changes in integrated health and social care through an analysis of local actions that were triggered by a national policy. A retrospective and qualitative case-study research design was used, and data from the model organisation's steering-committee minutes covering 1995-2015 were gathered and analysed. The analysis generated a narrative case description, which was mirrored to the key elements of the Dynamic Sustainability Framework (DSF). The development of inter-sectoral cooperation was characterized by a participatory approach in which a shared structure was created to support cooperation and on-going quality improvement and learning based on the needs of the service user. A key management principle was cooperation, not only on all organisational levels, but also with service users, stakeholder associations and other partner organisations. It was shown that all these parts were interrelated and collectively contributed to the creation of a structure and a culture which supported the development of a dynamic sustainable health and social care. This study provides valuable insights into the dynamics of organizational sustainability and understanding of key managerial actions taken to establish, develop and support integration of health and social care for people with complex mental health needs. The service user involvement and regular reviews of service users' needs were essential in order to tailor services to the needs. Another major finding was the importance of continuously adapting the content of the change to suit its context. Hence, continuous refinement of the change content was found to be more important than designing the change at the pre-implementation stage.

The Cloudy Crystal Ball: A Projection of the Nature of the University Counseling Center in the Year 2000.

ERIC Educational Resources Information Center

Maes, John L.

The nature of counseling in the year 2000 will be determined more by developing social needs than by existing programs. Since the direction of social development is toward increasingly dynamic, complex, and potentially stressful times, counseling services must be responsive to such conditions. The university counselor of the future will need to be…

a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems

NASA Astrophysics Data System (ADS)

Shao, Xiao; Chai, Li H.

As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.

Understanding the psychology of bullying: Moving toward a social-ecological diathesis-stress model.

PubMed

Swearer, Susan M; Hymel, Shelley

2015-01-01

With growing recognition that bullying is a complex phenomenon, influenced by multiple factors, research findings to date have been understood within a social-ecological framework. Consistent with this model, we review research on the known correlates and contributing factors in bullying/victimization within the individual, family, peer group, school and community. Recognizing the fluid and dynamic nature of involvement in bullying, we then expand on this model and consider research on the consequences of bullying involvement, as either victim or bully or both, and propose a social-ecological, diathesis-stress model for understanding the bullying dynamic and its impact. Specifically, we frame involvement in bullying as a stressful life event for both children who bully and those who are victimized, serving as a catalyst for a diathesis-stress connection between bullying, victimization, and psychosocial difficulties. Against this backdrop, we suggest that effective bullying prevention and intervention efforts must take into account the complexities of the human experience, addressing both individual characteristics and history of involvement in bullying, risk and protective factors, and the contexts in which bullying occurs, in order to promote healthier social relationships. (c) 2015 APA, all rights reserved).

Aging, memory, and nonhierarchical energy landscape of spin jam

PubMed Central

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-01-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes. PMID:27698141

Bullying Interventions: A Binocular Perspective

PubMed Central

Pepler, Debra J.

2006-01-01

Introduction Bullying is a complex relationship problem associated with many psychosocial difficulties for children who bully, as well as those who are victimized. A recent international volume of school-based bullying programs revealed modest effectiveness, highlighting the need to refine interventions using research on developmental profiles of children who bully and those who are victimized, as well as on their relationships. Method Based on developmental-systemic theory, a research review was conducted on individual and relationship risk factors associated with bullying and being victimized. Results The review led to the proposal of two organizing principles for interventions: Scaffolding and Social Architecture. Scaffolding focuses on providing tailored and dynamic supports for the needs of individual children who bully or who are victimized. Social architecture requires that adults focus on the social dynamics of children’s groups and create social contexts that promote positive peer interactions and dissipate contexts that foster negative interactions. Conclusion Interventions for bullying require a combination of scaffolding and social architecture to provide comprehensive supports and to change the social dynamics that enable bullying. With an empirically derived, comprehensive perspective, we may move closer to reducing the burden of these relationship problems in the lives of children and youth. PMID:18392191

Using cognitive architectures to study issues in team cognition in a complex task environment

NASA Astrophysics Data System (ADS)

Smart, Paul R.; Sycara, Katia; Tang, Yuqing

2014-05-01

Cognitive social simulation is a computer simulation technique that aims to improve our understanding of the dynamics of socially-situated and socially-distributed cognition. This makes cognitive social simulation techniques particularly appealing as a means to undertake experiments into team cognition. The current paper reports on the results of an ongoing effort to develop a cognitive social simulation capability that can be used to undertake studies into team cognition using the ACT-R cognitive architecture. This capability is intended to support simulation experiments using a team-based problem solving task, which has been used to explore the effect of different organizational environments on collective problem solving performance. The functionality of the ACT-R-based cognitive social simulation capability is presented and a number of areas of future development work are outlined. The paper also describes the motivation for adopting cognitive architectures in the context of social simulation experiments and presents a number of research areas where cognitive social simulation may be useful in developing a better understanding of the dynamics of team cognition. These include the use of cognitive social simulation to study the role of cognitive processes in determining aspects of communicative behavior, as well as the impact of communicative behavior on the shaping of task-relevant cognitive processes (e.g., the social shaping of individual and collective memory as a result of communicative exchanges). We suggest that the ability to perform cognitive social simulation experiments in these areas will help to elucidate some of the complex interactions that exist between cognitive, social, technological and informational factors in the context of team-based problem-solving activities.

Evidence of embodied social competence during conversation in high functioning children with autism spectrum disorder

PubMed Central

Fitzpatrick, Paula; Roulier, Stephanie; Duncan, Amie; Richardson, Michael J.; Schmidt, R. C.

2018-01-01

Even high functioning children with Autism Spectrum Disorder (ASD) exhibit impairments that affect their ability to carry out and maintain effective social interactions in multiple contexts. One aspect of subtle nonverbal communication that might play a role in this impairment is the whole-body motor coordination that naturally arises between people during conversation. The current study aimed to measure the time-dependent, coordinated whole-body movements between children with ASD and a clinician during a conversational exchange using tools of nonlinear dynamics. Given the influence that subtle interpersonal coordination has on social interaction feelings, we expected there to be important associations between the dynamic motor movement measures introduced in the current study and the measures used traditionally to categorize ASD impairment (ADOS-2, joint attention and theory of mind). The study found that children with ASD coordinated their bodily movements with a clinician, that these movements were complex and that the complexity of the children’s movements matched that of the clinician’s movements. Importantly, the degree of this bodily coordination was related to higher social cognitive ability. This suggests children with ASD are embodying some degree of social competence during conversations. This study demonstrates the importance of further investigating the subtle but important bodily movement coordination that occurs during social interaction in children with ASD. PMID:29505608

Recent social and biogeophysical changes in the Ganges-Brahmaputra-Meghna, Mekong, and Amazon deltas as inputs into evolutionary policy-making.

NASA Astrophysics Data System (ADS)

de Araujo Barbosa, C. C.; Hossain, S.; Szabo, S.; Matthews, Z.; Heard, S.; Dearing, J.

2014-12-01

Policy-making in social-ecological systems increasingly looks to iterative, evolutionary approaches that can address the inherent complexity of interactions between human wellbeing, agricultural and aquacultural production, and ecosystem services. Here we show how an analysis of available time-series in delta regions over past decades can provide important insight into the social-ecological system dynamics that result from the complexity. The presentation summarises the recent changes for major elements of each social-ecological system, for example demography, economy, health, climate, food, and water. Time-series data from official statistics, monitoring programmes and sequential satellite imagery are analysed to define the range of trends, the presence of change points, slow and fast variables, and the significant drivers of change. For example, in the Bangladesh delta zone, increasing gross domestic product and per capita income levels since the 1980s mirror rising levels of food and inland fish production. In contrast, non-food ecosystem services such as water availability, water quality and land stability have deteriorated. As a result, poverty alleviation is associated with environmental degradation. Trends in indicators of human wellbeing and ecosystem services point to widespread non-stationary dynamics governed by slowly changing variables with increased probability of systemic threshold changes/tipping points in the near future. We conclude by examining how the findings could feed into new management tools, such as system dynamic models and assessments of safe operating spaces. Such tools have the potential to help create policies that deliver alternative and sustainable paths for land management while accommodating social and environmental change.

Evidence for an audience effect in mice: male social partners alter the male vocal response to female cues

PubMed Central

Seagraves, Kelly M.; Arthur, Ben J.; Egnor, S. E. Roian

2016-01-01

ABSTRACT Mice (Mus musculus) form large and dynamic social groups and emit ultrasonic vocalizations in a variety of social contexts. Surprisingly, these vocalizations have been studied almost exclusively in the context of cues from only one social partner, despite the observation that in many social species the presence of additional listeners changes the structure of communication signals. Here, we show that male vocal behavior elicited by female odor is affected by the presence of a male audience – with changes in vocalization count, acoustic structure and syllable complexity. We further show that single sensory cues are not sufficient to elicit this audience effect, indicating that multiple cues may be necessary for an audience to be apparent. Together, these experiments reveal that some features of mouse vocal behavior are only expressed in more complex social situations, and introduce a powerful new assay for measuring detection of the presence of social partners in mice. PMID:27207951

Evidence for an audience effect in mice: male social partners alter the male vocal response to female cues.

PubMed

Seagraves, Kelly M; Arthur, Ben J; Egnor, S E Roian

2016-05-15

Mice (Mus musculus) form large and dynamic social groups and emit ultrasonic vocalizations in a variety of social contexts. Surprisingly, these vocalizations have been studied almost exclusively in the context of cues from only one social partner, despite the observation that in many social species the presence of additional listeners changes the structure of communication signals. Here, we show that male vocal behavior elicited by female odor is affected by the presence of a male audience - with changes in vocalization count, acoustic structure and syllable complexity. We further show that single sensory cues are not sufficient to elicit this audience effect, indicating that multiple cues may be necessary for an audience to be apparent. Together, these experiments reveal that some features of mouse vocal behavior are only expressed in more complex social situations, and introduce a powerful new assay for measuring detection of the presence of social partners in mice. © 2016. Published by The Company of Biologists Ltd.

A framework for complexity in palliative care: A qualitative study with patients, family carers and professionals.

PubMed

Pask, Sophie; Pinto, Cathryn; Bristowe, Katherine; van Vliet, Liesbeth; Nicholson, Caroline; Evans, Catherine J; George, Rob; Bailey, Katharine; Davies, Joanna M; Guo, Ping; Daveson, Barbara A; Higginson, Irene J; Murtagh, Fliss Em

2018-06-01

Palliative care patients are often described as complex but evidence on complexity is limited. We need to understand complexity, including at individual patient-level, to define specialist palliative care, characterise palliative care populations and meaningfully compare interventions/outcomes. To explore palliative care stakeholders' views on what makes a patient more or less complex and insights on capturing complexity at patient-level. In-depth qualitative interviews, analysed using Framework analysis. Semi-structured interviews across six UK centres with patients, family, professionals, managers and senior leads, purposively sampled by experience, background, location and setting (hospital, hospice and community). 65 participants provided an understanding of complexity, which extended far beyond the commonly used physical, psychological, social and spiritual domains. Complexity included how patients interact with family/professionals, how services' respond to needs and societal perspectives on care. 'Pre-existing', 'cumulative' and 'invisible' complexity are further important dimensions to delivering effective palliative and end-of-life care. The dynamic nature of illness and needs over time was also profoundly influential. Adapting Bronfenbrenner's Ecological Systems Theory, we categorised findings into the microsystem (person, needs and characteristics), chronosystem (dynamic influences of time), mesosystem (interactions with family/health professionals), exosystem (palliative care services/systems) and macrosystem (societal influences). Stakeholders found it acceptable to capture complexity at the patient-level, with perceived benefits for improving palliative care resource allocation. Our conceptual framework encompasses additional elements beyond physical, psychological, social and spiritual domains and advances systematic understanding of complexity within the context of palliative care. This framework helps capture patient-level complexity and target resource provision in specialist palliative care.

Dynamical Resilience Indicators in Time Series of Self-Rated Health Correspond to Frailty Levels in Older Adults.

PubMed

Gijzel, Sanne M W; van de Leemput, Ingrid A; Scheffer, Marten; Roppolo, Mattia; Olde Rikkert, Marcel G M; Melis, René J F

2017-07-01

We currently still lack valid methods to dynamically measure resilience for stressors before the appearance of adverse health outcomes that hamper well-being. Quantifying an older adult's resilience in an early stage would aid complex decision-making in health care. Translating complex dynamical systems theory to humans, we hypothesized that three dynamical indicators of resilience (variance, temporal autocorrelation, and cross-correlation) in time series of self-rated physical, mental, and social health were associated with frailty levels in older adults. We monitored self-rated physical, mental, and social health during 100 days using daily visual analogue scale questions in 22 institutionalized older adults (mean age 84.0, SD: 5.9 years). Frailty was determined by the Survey of Health, Ageing and Retirement in Europe (SHARE) frailty index. The resilience indicators (variance, temporal autocorrelation, and cross-correlation) were calculated using multilevel models. The self-rated health time series of frail elderly exhibited significantly elevated variance in the physical, mental, and social domain, as well as significantly stronger cross-correlations between all three domains, as compared to the nonfrail group (all P < 0.001). Temporal autocorrelation was not significantly associated with frailty. We found supporting evidence for two out of three hypothesized resilience indicators to be related to frailty levels in older adults. By mirroring the dynamical resilience indicators to a frailty index, we delivered a first empirical base to validate and quantify the construct of systemic resilience in older adults in a dynamic way. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks.

PubMed

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks

NASA Astrophysics Data System (ADS)

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Proceedings of the Agent 2002 Conference on Social Agents : Ecology, Exchange, and Evolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Macal, C., ed.; Sallach, D., ed.

2003-04-10

Welcome to the ''Proceedings'' of the third in a series of agent simulation conferences cosponsored by Argonne National Laboratory and The University of Chicago. The theme of this year's conference, ''Social Agents: Ecology, Exchange and Evolution'', was selected to foster the exchange of ideas on some of the most important social processes addressed by agent simulation models, namely: (1) The translation of ecology and ecological constraints into social dynamics; (2) The role of exchange processes, including the peer dependencies they create; and (3) The dynamics by which, and the attractor states toward which, social processes evolve. As stated in themore » ''Call for Papers'', throughout the social sciences, the simulation of social agents has emerged as an innovative and powerful research methodology. The promise of this approach, however, is accompanied by many challenges. First, modeling complexity in agents, environments, and interactions is non-trivial, and these representations must be explored and assessed systematically. Second, strategies used to represent complexities are differentially applicable to any particular problem space. Finally, to achieve sufficient generality, the design and experimentation inherent in agent simulation must be coupled with social and behavioral theory. Agent 2002 provides a forum for reviewing the current state of agent simulation scholarship, including research designed to address such outstanding issues. This year's conference introduces an extensive range of domains, models, and issues--from pre-literacy to future projections, from ecology to oligopolistic markets, and from design to validation. Four invited speakers highlighted major themes emerging from social agent simulation.« less

Alternative stable states and the sustainability of forests, grasslands, and agriculture

PubMed Central

Henderson, Kirsten A.; Bauch, Chris T.; Anand, Madhur

2016-01-01

Endangered forest–grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human–environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations—especially for forests—due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human–environment mosaic ecosystems. PMID:27956605

Alternative stable states and the sustainability of forests, grasslands, and agriculture.

PubMed

Henderson, Kirsten A; Bauch, Chris T; Anand, Madhur

2016-12-20

Endangered forest-grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human-environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations-especially for forests-due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human-environment mosaic ecosystems.

Social and economic influences on human behavioural response in an emerging epidemic

NASA Astrophysics Data System (ADS)

Phang, P.; Wiwatanapataphee, B.; Wu, Y. H.

2017-10-01

The human behavioural changes have been recognized as an important key in shaping the disease spreading and determining the success of control measures in the course of epidemic outbreaks. However, apart from cost-benefit considerations, in reality, people are heterogeneous in their preferences towards adopting certain protective actions to reduce their risk of infection, and social norms have a function in individuals’ decision making. Here, we studied the interplay between the epidemic dynamics, imitation dynamics and the heterogeneity of individual protective behavioural response under the considerations of both economic and social factors, with a simple mathematical compartmental model and multi-population game dynamical replicator equations. We assume that susceptibles in different subpopulations have different preferences in adopting either normal or altered behaviour. By incorporating both intra- and inter-group social pressure, the outcome of the strategy distribution depends on the initial proportion of susceptible with normal and altered strategies in both subpopulations. The increase of additional cost to susceptible with altered behaviour will discourage people to take up protective actions and hence results in higher epidemic final size. For a specific cost of altered behaviour, the social group pressure could be a “double edge sword”, though. We conclude that the interplays between individual protective behaviour adoption, imitation and epidemic dynamics are necessarily complex if both economic and social factors act on populations with existing preferences.

Complex contagion process in spreading of online innovation.

PubMed

Karsai, Márton; Iñiguez, Gerardo; Kaski, Kimmo; Kertész, János

2014-12-06

Diffusion of innovation can be interpreted as a social spreading phenomenon governed by the impact of media and social interactions. Although these mechanisms have been identified by quantitative theories, their role and relative importance are not entirely understood, as empirical verification has so far been hindered by the lack of appropriate data. Here we analyse a dataset recording the spreading dynamics of the world's largest Voice over Internet Protocol service to empirically support the assumptions behind models of social contagion. We show that the rate of spontaneous service adoption is constant, the probability of adoption via social influence is linearly proportional to the fraction of adopting neighbours, and the rate of service termination is time-invariant and independent of the behaviour of peers. By implementing the detected diffusion mechanisms into a dynamical agent-based model, we are able to emulate the adoption dynamics of the service in several countries worldwide. This approach enables us to make medium-term predictions of service adoption and disclose dependencies between the dynamics of innovation spreading and the socio-economic development of a country. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts.

PubMed

Lade, Steven J; Niiranen, Susa; Hentati-Sundberg, Jonas; Blenckner, Thorsten; Boonstra, Wiebren J; Orach, Kirill; Quaas, Martin F; Österblom, Henrik; Schlüter, Maja

2015-09-01

Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social-ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social-ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social-ecological models.

Challenges in network science: Applications to infrastructures, climate, social systems and economics

NASA Astrophysics Data System (ADS)

Havlin, S.; Kenett, D. Y.; Ben-Jacob, E.; Bunde, A.; Cohen, R.; Hermann, H.; Kantelhardt, J. W.; Kertész, J.; Kirkpatrick, S.; Kurths, J.; Portugali, J.; Solomon, S.

2012-11-01

Network theory has become one of the most visible theoretical frameworks that can be applied to the description, analysis, understanding, design and repair of multi-level complex systems. Complex networks occur everywhere, in man-made and human social systems, in organic and inorganic matter, from nano to macro scales, and in natural and anthropogenic structures. New applications are developed at an ever-increasing rate and the promise for future growth is high, since increasingly we interact with one another within these vital and complex environments. Despite all the great successes of this field, crucial aspects of multi-level complex systems have been largely ignored. Important challenges of network science are to take into account many of these missing realistic features such as strong coupling between networks (networks are not isolated), the dynamics of networks (networks are not static), interrelationships between structure, dynamics and function of networks, interdependencies in given networks (and other classes of links, including different signs of interactions), and spatial properties (including geographical aspects) of networks. This aim of this paper is to introduce and discuss the challenges that future network science needs to address, and how different disciplines will be accordingly affected.

The role of the right hemisphere for processing of social interactions in normal adults using functional magnetic resonance imaging.

PubMed

Semrud-Clikeman, Margaret; Fine, Jodene Goldenring; Zhu, David C

2011-01-01

The main purpose of this study was to evaluate whole-brain and hemispheric activation in normal adult volunteers to videos depicting positive and negative social encounters. There are few studies that have utilized dynamic social stimuli to evaluate brain activation. Twenty young adults viewed videotaped vignettes during an functional magnetic resonance imaging procedure. The vignettes included positive and negative interaction scenes of social encounters. Significant right greater than left activation for positive and negative conditions was found for the social interaction videos in the amygdaloid complex, the inferior frontal gyrus, the fusiform gyrus, and the temporal gyri (p < 0.0001). These findings support the hypothesis that the regions of the right hemisphere are more active in the interpretation of social information processing than those regions in the left hemisphere. This study is a first step in understanding processing of dynamic stimuli using ecologically appropriate stimuli that approximate the real-time social processing that is appropriate for use with populations who experience significant social problems. Copyright © 2011 S. Karger AG, Basel.

System dynamic simulation: A new method in social impact assessment (SIA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karami, Shobeir, E-mail: shobeirkarami@gmail.com; Karami, Ezatollah, E-mail: ekarami@shirazu.ac.ir; Buys, Laurie, E-mail: l.buys@qut.edu.au

Many complex social questions are difficult to address adequately with conventional methods and techniques, due to the complicated dynamics, and hard to quantify social processes. Despite these difficulties researchers and practitioners have attempted to use conventional methods not only in evaluative modes but also in predictive modes to inform decision making. The effectiveness of SIAs would be increased if they were used to support the project design processes. This requires deliberate use of lessons from retrospective assessments to inform predictive assessments. Social simulations may be a useful tool for developing a predictive SIA method. There have been limited attempts tomore » develop computer simulations that allow social impacts to be explored and understood before implementing development projects. In light of this argument, this paper aims to introduce system dynamic (SD) simulation as a new predictive SIA method in large development projects. We propose the potential value of the SD approach to simulate social impacts of development projects. We use data from the SIA of Gareh-Bygone floodwater spreading project to illustrate the potential of SD simulation in SIA. It was concluded that in comparison to traditional SIA methods SD simulation can integrate quantitative and qualitative inputs from different sources and methods and provides a more effective and dynamic assessment of social impacts for development projects. We recommend future research to investigate the full potential of SD in SIA in comparing different situations and scenarios.« less

Emotional contagion and proto-organizing in human interaction dynamics

PubMed Central

Hazy, James K.; Boyatzis, Richard E.

2015-01-01

This paper combines the complexity notions of phase transitions and tipping points with recent advances in cognitive neuroscience to propose a general theory of human proto-organizing. It takes as a premise that a necessary prerequisite for organizing, or “proto-organizing,” occurs through emotional contagion in subpopulations of human interaction dynamics in complex ecosystems. Emotional contagion is posited to engender emotional understanding and identification with others, a social process that acts as a mechanism that enables (or precludes) cooperative responses to opportunities and risks. Propositions are offered and further research is suggested. PMID:26124736

A mass assembly of associative mechanisms: a dynamical systems account of natural social interaction.

PubMed

Duran, Nicholas D; Dale, Rick; Richardson, Daniel C

2014-04-01

The target article offers a negative, eliminativist thesis, dissolving the specialness of mirroring processes into a solution of associative mechanisms. We support the authors' project enthusiastically. What they are currently missing, we argue, is a positive, generative thesis about associative learning mechanisms and how they might give way to the complex, multimodal coordination that naturally arises in social interaction.

The interplay between interpersonal dynamics, treatment barriers, and larger social forces: an exploratory study of drug-using couples in Hartford, CT

PubMed Central

Simmons, Janie

2006-01-01

Background The drug treatment field tends to place emphasis on the individual rather than the individual in social context. While there are a growing number of studies indicating that drug-using intimate partners are likely to play an important role in determining treatment options, little attention has been given to the experience and complex treatment needs of illicit drug-using (heroin, cocaine, crack) couples. Methods This exploratory study used in-depth interviews and ethnographic engagement to better understand the relationship between interpersonal dynamics and the treatment experience of ten relatively stable drug-using couples in Hartford, CT. Semi-structured and open-ended qualitative interviews were conducted with each couple and separately with each partner. Whenever possible, the day-to-day realities and contexts of risk were also observed via participant and non-participant observation of these couples in the community. A grounded theory approach was used to inductively code and analyze nearly 40 transcripts of 60–90 minute interviews as well as fieldnotes. Results This study builds on a concept of complex interpersonal dynamics among drug users. Interpersonal dynamics of care and collusion were identified: couples cared for each other and colluded to acquire and use drugs. Care and collusion operate at the micro level of the risk environment. Treatment barriers and inadequacies were identified as part of the risk environment at the meso or intermediate level of analysis, and larger social forces such as gender dynamics, poverty and the "War on Drugs" were identified at the macro level. Interpersonal dynamics posed problems for couples when one or both partners were interested in accessing treatment. Structural barriers presented additional obstacles with the denial of admittance of both partners to treatment programs which had a sole focus on the individual and avoided treating couples. Conclusion Detoxification and treatment facilities need to recognize the complex interplay between interpersonal dynamics which shape the treatment experience of couples, and which are also shaped by larger structural dynamics, including barriers in the treatment system. Improvements to the treatment system in general will go a long way in improving treatment for couples. Couples-specific programming also needs to be developed. PMID:16722545

A Dynamic Game on Network Topology for Counterinsurgency Applications

DTIC Science & Technology

2015-03-26

scenario. This study creates a dynamic game on network topology to provide insight into the effec- tiveness of offensive targeting strategies determined by...focused upon the diffusion of thoughts and innovations throughout complex social networks. Coleman et al. (1966) and Ryan & Gross (1950) investigated...free networks make them extremely resilient against errors but very vulnerable to attack. Most interest- ingly, a determined attacker can remove well

Discriminative Justice: Can Discrimination Be Just?

ERIC Educational Resources Information Center

Rocco, Tonette S.; Gallagher, Suzanne J.

2004-01-01

Educators of urban adults should attempt to deconstruct the dynamics in the classroom that replicate the social, political, and economic discourse of the dominant group. We must work to surface the complexity of diverse experiences represented by multiple oppressed groups.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Constructing food choice decisions.

PubMed

Sobal, Jeffery; Bisogni, Carole A

2009-12-01

Food choice decisions are frequent, multifaceted, situational, dynamic, and complex and lead to food behaviors where people acquire, prepare, serve, give away, store, eat, and clean up. Many disciplines and fields examine decision making. Several classes of theories are applicable to food decision making, including social behavior, social facts, and social definition perspectives. Each offers some insights but also makes limiting assumptions that prevent fully explaining food choice decisions. We used constructionist social definition perspectives to inductively develop a food choice process model that organizes a broad scope of factors and dynamics involved in food behaviors. This food choice process model includes (1) life course events and experiences that establish a food choice trajectory through transitions, turning points, timing, and contexts; (2) influences on food choices that include cultural ideals, personal factors, resources, social factors, and present contexts; and (3) a personal system that develops food choice values, negotiates and balances values, classifies foods and situations, and forms/revises food choice strategies, scripts, and routines. The parts of the model dynamically interact to make food choice decisions leading to food behaviors. No single theory can fully explain decision making in food behavior. Multiple perspectives are needed, including constructionist thinking.

Agent-based modeling: a new approach for theory building in social psychology.

PubMed

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Assessing sustainability in real urban systems: the Greater Cincinnati Metropolitan Area in Ohio, Kentucky, and Indiana.

PubMed

Gonzalez-Mejía, Alejandra M; Eason, Tarsha N; Cabezas, Heriberto; Suidan, Makram T

2012-09-04

Urban systems have a number of factors (i.e., economic, social, and environmental) that can potentially impact growth, change, and transition. As such, assessing and managing these systems is a complex challenge. While, tracking trends of key variables may provide some insight, identifying the critical characteristics that truly impact the dynamic behavior of these systems is difficult. As an integrated approach to evaluate real urban systems, this work contributes to the research on scientific techniques for assessing sustainability. Specifically, it proposes a practical methodology based on the estimation of dynamic order, for identifying stable and unstable periods of sustainable or unsustainable trends with Fisher Information (FI) metric. As a test case, the dynamic behavior of the City, Suburbs, and Metropolitan Statistical Area (MSA) of Cincinnati was evaluated by using 29 social and 11 economic variables to characterize each system from 1970 to 2009. Air quality variables were also selected to describe the MSA's environmental component (1980-2009). Results indicate systems dynamic started to change from about 1995 for the social variables and about 2000 for the economic and environmental characteristics.

The U.S. Army Functional Concept for Intelligence 2020-2040

DTIC Science & Technology

2017-02-01

Soldiers to mitigate many complex problems of the future OE. Improved or new analytic processes will use very large data sets to address emerging...increasing. Army collection against publically available data sources may offer insights to social interconnectedness, political dynamics and complex... data used to support situational understanding. (5) Uncertainty and rapid change elevate the analytic risk associated with decision making and

Social complexity, modernity and suicide: an assessment of Durkheim's suicide from the perspective of a non-linear analysis of complex social systems.

PubMed

Condorelli, Rosalia

2016-01-01

Can we share even today the same vision of modernity which Durkheim left us by its suicide analysis? or can society 'surprise us'? The answer to these questions can be inspired by several studies which found that beginning the second half of the twentieth century suicides in western countries more industrialized and modernized do not increase in a constant, linear way as modernization and social fragmentation process increases, as well as Durkheim's theory seems to lead us to predict. Despite continued modernizing process, they found stabilizing or falling overall suicide rate trends. Therefore, a gradual process of adaptation to the stress of modernization associated to low social integration levels seems to be activated in modern society. Assuming this perspective, the paper highlights as this tendency may be understood in the light of the new concept of social systems as complex adaptive systems, systems which are able to adapt to environmental perturbations and generate as a whole surprising, emergent effects due to nonlinear interactions among their components. So, in the frame of Nonlinear Dynamical System Modeling, we formalize the logic of suicide decision-making process responsible for changes at aggregate level in suicide growth rates by a nonlinear differential equation structured in a logistic way, and in so doing we attempt to capture the mechanism underlying the change process in suicide growth rate and to test the hypothesis that system's dynamics exhibits a restrained increase process as expression of an adaptation process to the liquidity of social ties in modern society. In particular, a Nonlinear Logistic Map is applied to suicide data in a modern society such as the Italian one from 1875 to 2010. The analytic results, seeming to confirm the idea of the activation of an adaptation process to the liquidity of social ties, constitutes an opportunity for a more general reflection on the current configuration of modern society, by relating the Durkheimian Theory with the Halbwachs' Theory and most current visions of modernity such as the Baumanian one. Complexity completes the interpretative framework by rooting the generating mechanism of adaptation process in the precondition of a new General Theory of Systems making the non linearity property of social system's interactions and surprise the functioning and evolution rule of social systems.

Stochastic Dynamics through Hierarchically Embedded Markov Chains

NASA Astrophysics Data System (ADS)

Vasconcelos, Vítor V.; Santos, Fernando P.; Santos, Francisco C.; Pacheco, Jorge M.

2017-02-01

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects—such as mutations in evolutionary dynamics and a random exploration of choices in social systems—including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Stochastic Dynamics through Hierarchically Embedded Markov Chains.

PubMed

Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

2017-02-03

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Leo Szilard Lectureship Award Talk - Universal Scaling Laws from Cells to Cities; A Physicist's Search for Quantitative, Unified Theories of Biological and Social Structure and Dynamics

NASA Astrophysics Data System (ADS)

West, Geoffrey

2013-04-01

Many of the most challenging, exciting and profound questions facing science and society, from the origins of life to global sustainability, fall under the banner of ``complex adaptive systems.'' This talk explores how scaling can be used to begin to develop physics-inspired quantitative, predictive, coarse-grained theories for understanding their structure, dynamics and organization based on underlying mathematisable principles. Remarkably, most physiological, organisational and life history phenomena in biology and socio-economic systems scale in a simple and ``universal'' fashion: metabolic rate scales approximately as the 3/4-power of mass over 27 orders of magnitude from complex molecules to the largest organisms. Time-scales (such as lifespans and growth-rates) and sizes (such as genome lengths and RNA densities) scale with exponents which are typically simple multiples of 1/4, suggesting that fundamental constraints underlie much of the generic structure and dynamics of living systems. These scaling laws follow from dynamical and geometrical properties of space-filling, fractal-like, hierarchical branching networks, presumed optimised by natural selection. This leads to a general framework that potentially captures essential features of diverse systems including vasculature, ontogenetic growth, cancer, aging and mortality, sleep, cell size, and DNA nucleotide substitution rates. Cities and companies also scale: wages, profits, patents, crime, disease, pollution, road lengths scale similarly across the globe, reflecting underlying universal social network dynamics which point to general principles of organization transcending their individuality. These have dramatic implications for global sustainability: innovation and wealth creation that fuel social systems, left unchecked, potentially sow the seeds for their inevitable collapse.

Towards a Moral Ecology of Pharmacological Cognitive Enhancement in British Universities.

PubMed

Vagwala, Meghana Kasturi; Bicquelet, Aude; Didziokaite, Gabija; Coomber, Ross; Corrigan, Oonagh; Singh, Ilina

2017-01-01

Few empirical studies in the UK have examined the complex social patterns and values behind quantitative estimates of the prevalence of pharmacological cognitive enhancement (PCE). We conducted a qualitative investigation of the social dynamics and moral attitudes that shape PCE practices among university students in two major metropolitan areas in the UK. Our thematic analysis of eight focus groups ( n  = 66) suggests a moral ecology that operates within the social infrastructure of the university. We find that PCE resilience among UK university students is mediated by normative and cultural judgments disfavoring competitiveness and prescription drug taking. PCE risk can be augmented by social factors such as soft peer pressure and normalization of enhancement within social and institutional networks. We suggest that moral ecological dynamics should be viewed as key mechanisms of PCE risk and resilience in universities. Effective PCE governance within universities should therefore attend to developing further understanding of the moral ecologies of PCE.

[Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

PubMed

Díaz Córdova, Diego

2016-01-01

The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

From the Teachers' Eyes: An Ethnographic-Case Study on Developing Models of Informal Formative Assessments (IFA) and Understanding the Challenges to Effective Implementation in Science Classrooms

ERIC Educational Resources Information Center

Sezen, Asli

2011-01-01

The emphasis on socio-cultural theories of learning has required the understanding of multi-dimensional, dynamic and social nature of acquiring the scientific knowledge and practices. Recent policy documents suggest a focus on formative and dynamic assessment practices that will help understand and improve the complex nature of scientific learning…

Host social organization and mating system shape parasite transmission opportunities in three European bat species.

PubMed

van Schaik, J; Kerth, G

2017-02-01

For non-mobile parasites living on social hosts, infection dynamics are strongly influenced by host life history and social system. We explore the impact of host social systems on parasite population dynamics by comparing the infection intensity and transmission opportunities of three mite species of the genus Spinturnix across their three European bat hosts (Myotis daubentonii, Myotis myotis, Myotis nattereri) during the bats' autumn mating season. Mites mainly reproduce in host maternity colonies in summer, but as these colonies are closed, opportunities for inter-colony transmission are limited to host interactions during the autumn mating season. The three investigated hosts differ considerably in their social system, most notably in maternity colony size, mating system, and degree of male summer aggregation. We observed marked differences in parasite infection during the autumn mating period between the species, closely mirroring the predictions made based on the social systems of the hosts. Increased host aggregation sizes in summer yielded higher overall parasite prevalence and intensity, both in male and female hosts. Moreover, parasite levels in male hosts differentially increased throughout the autumn mating season in concordance with the degree of contact with female hosts afforded by the different mating systems of the hosts. Critically, the observed host-specific differences have important consequences for parasite population structure and will thus affect the coevolutionary dynamics between the interacting species. Therefore, in order to accurately characterize host-parasite dynamics in hosts with complex social systems, a holistic approach that investigates parasite infection and transmission across all periods is warranted.

Epidemic dynamics and endemic states in complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2001-06-01

We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Communicating science in social settings.

PubMed

Scheufele, Dietram A

2013-08-20

This essay examines the societal dynamics surrounding modern science. It first discusses a number of challenges facing any effort to communicate science in social environments: lay publics with varying levels of preparedness for fully understanding new scientific breakthroughs; the deterioration of traditional media infrastructures; and an increasingly complex set of emerging technologies that are surrounded by a host of ethical, legal, and social considerations. Based on this overview, I discuss four areas in which empirical social science helps clarify intuitive but sometimes faulty assumptions about the social-level mechanisms of science communication and outline an agenda for bench and social scientists--driven by current social-scientific research in the field of science communication--to guide more effective communication efforts at the societal level in the future.

Communicating science in social settings

PubMed Central

Scheufele, Dietram A.

2013-01-01

This essay examines the societal dynamics surrounding modern science. It first discusses a number of challenges facing any effort to communicate science in social environments: lay publics with varying levels of preparedness for fully understanding new scientific breakthroughs; the deterioration of traditional media infrastructures; and an increasingly complex set of emerging technologies that are surrounded by a host of ethical, legal, and social considerations. Based on this overview, I discuss four areas in which empirical social science helps clarify intuitive but sometimes faulty assumptions about the social-level mechanisms of science communication and outline an agenda for bench and social scientists—driven by current social-scientific research in the field of science communication—to guide more effective communication efforts at the societal level in the future. PMID:23940341

Community evolution mining and analysis in social network

NASA Astrophysics Data System (ADS)

Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

2017-03-01

With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

Perc, Matjaž; Gómez-Gardeñes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir

2013-01-01

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223

Understanding Patterns of Social Support and Their Relationship to an ART Adherence Intervention Among Adults in Rural Southwestern Uganda.

PubMed

Atukunda, Esther C; Musiimenta, Angella; Musinguzi, Nicholas; Wyatt, Monique A; Ashaba, Justus; Ware, Norma C; Haberer, Jessica E

2017-02-01

SMS is a widely used technology globally and may also improve ART adherence, yet SMS notifications to social supporters following real-time detection of missed doses showed no clear benefit in a recent pilot trial. We examine the demographic and social-cultural dynamics that may explain this finding. In the trial, 63 HIV-positive individuals initiating ART received a real-time adherence monitor and were randomized to two types of SMS reminder interventions versus a control (no SMS). SMS notifications were also sent to 45 patient-identified social supporters for sustained adherence lapses. Like participants, social supporters were interviewed at enrollment, following their matched participant's adherence lapse and at exit. Social supporters with regular income (RR = 0.27, P = 0.001) were significantly associated with fewer adherence lapses. Instrumental support was associated with fewer adherence lapses only among social supporters who were food secure (RR = 0.58, P = 0.003). Qualitative interview data revealed diverse and complex economic and relationship dynamics, affecting social support. Resource availability in emotionally positive relationships seemingly facilitated helpful support, while limited resources prevented active provision of support for many. Effective social support appeared subject to social supporters' food security, economic stability and a well-functioning social network dependent on trust and supportive disclosure.

Collective phenomena in crowds—Where pedestrian dynamics need social psychology

PubMed Central

2017-01-01

This article is on collective phenomena in pedestrian dynamics during the assembling and dispersal of gatherings. To date pedestrian dynamics have been primarily studied in the natural and engineering sciences. Pedestrians are analyzed and modeled as driven particles revealing self-organizing phenomena and complex transport characteristics. However, pedestrians in crowds also behave as living beings according to stimulus-response mechanisms or act as human subjects on the basis of social norms, social identities or strategies. To show where pedestrian dynamics need social psychology in addition to the natural sciences we propose the application of three categories–phenomena, behavior and action. They permit a clear discrimination between situations in which minimal models from the natural sciences are appropriate and those in which sociological and psychological concepts are needed. To demonstrate the necessity of this framework, an experiment in which a large group of people (n = 270) enters a concert hall through two different spatial barrier structures is analyzed. These two structures correspond to everyday situations such as boarding trains and access to immigration desks. Methods from the natural and social sciences are applied. Firstly, physical measurements show the influence of the spatial structure on the dynamics of the entrance procedure. Density, waiting time and speed of progress show large variations. Secondly, a questionnaire study (n = 60) reveals how people perceive and evaluate these entrance situations. Markedly different expectations, social norms and strategies are associated with the two spatial structures. The results from the questionnaire study do not always conform to objective physical measures, indicating the limitations of models which are based on objective physical measures alone and which neglect subjective perspectives. PMID:28591142

Collective phenomena in crowds-Where pedestrian dynamics need social psychology.

PubMed

Sieben, Anna; Schumann, Jette; Seyfried, Armin

2017-01-01

This article is on collective phenomena in pedestrian dynamics during the assembling and dispersal of gatherings. To date pedestrian dynamics have been primarily studied in the natural and engineering sciences. Pedestrians are analyzed and modeled as driven particles revealing self-organizing phenomena and complex transport characteristics. However, pedestrians in crowds also behave as living beings according to stimulus-response mechanisms or act as human subjects on the basis of social norms, social identities or strategies. To show where pedestrian dynamics need social psychology in addition to the natural sciences we propose the application of three categories-phenomena, behavior and action. They permit a clear discrimination between situations in which minimal models from the natural sciences are appropriate and those in which sociological and psychological concepts are needed. To demonstrate the necessity of this framework, an experiment in which a large group of people (n = 270) enters a concert hall through two different spatial barrier structures is analyzed. These two structures correspond to everyday situations such as boarding trains and access to immigration desks. Methods from the natural and social sciences are applied. Firstly, physical measurements show the influence of the spatial structure on the dynamics of the entrance procedure. Density, waiting time and speed of progress show large variations. Secondly, a questionnaire study (n = 60) reveals how people perceive and evaluate these entrance situations. Markedly different expectations, social norms and strategies are associated with the two spatial structures. The results from the questionnaire study do not always conform to objective physical measures, indicating the limitations of models which are based on objective physical measures alone and which neglect subjective perspectives.

Further steps in the modeling of behavioural crowd dynamics, good news for safe handling. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Knopoff, Damián A.

2016-09-01

The recent review paper [4] constitutes a valuable contribution on the understanding, modeling and simulation of crowd dynamics in extreme situations. It provides a very comprehensive revision about the complexity features of the system under consideration, scaling and the consequent justification of the used methods. In particular, macro and microscopic models have so far been used to model crowd dynamics [9] and authors appropriately explain that working at the mesoscale is a good choice to deal with the heterogeneous behaviour of walkers as well as with the difficulty of their deterministic identification. In this way, methods based on the kinetic theory and statistical dynamics are employed, more precisely the so-called kinetic theory for active particles [7]. This approach has successfully been applied in the modeling of several complex dynamics, with recent applications to learning [2,8] that constitutes the key to understand communication and is of great importance in social dynamics and behavioral sciences.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena.

PubMed

De Domenico, Manlio

2017-04-21

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Controlling herding in minority game systems

NASA Astrophysics Data System (ADS)

Zhang, Ji-Qiang; Huang, Zi-Gang; Wu, Zhi-Xi; Su, Riqi; Lai, Ying-Cheng

2016-02-01

Resource allocation takes place in various types of real-world complex systems such as urban traffic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of resource allocation can be modeled as minority games. Spontaneous evolution of the resource allocation dynamics, however, often leads to a harmful herding behavior accompanied by strong fluctuations in which a large majority of agents crowd temporarily for a few resources, leaving many others unused. Developing effective control methods to suppress and eliminate herding is an important but open problem. Here we develop a pinning control method, that the fluctuations of the system consist of intrinsic and systematic components allows us to design a control scheme with separated control variables. A striking finding is the universal existence of an optimal pinning fraction to minimize the variance of the system, regardless of the pinning patterns and the network topology. We carry out a generally applicable theory to explain the emergence of optimal pinning and to predict the dependence of the optimal pinning fraction on the network topology. Our work represents a general framework to deal with the broader problem of controlling collective dynamics in complex systems with potential applications in social, economical and political systems.

Regime shifts and panarchies in regional scale social-ecological water systems

EPA Science Inventory

In this article we summarize histories of nonlinear, complex interactions among societal, legal, and ecosystem dynamics in six North American water basins, as they respond to changing climate. These case studies were chosen to explore the conditions for emergence of adaptive gove...

Can Multilayer Networks Advance Animal Behavior Research?

PubMed

Silk, Matthew J; Finn, Kelly R; Porter, Mason A; Pinter-Wollman, Noa

2018-06-01

Interactions among individual animals - and between these individuals and their environment - yield complex, multifaceted systems. The development of multilayer network analysis offers a promising new approach for studying animal social behavior and its relation to eco-evolutionary dynamics. Copyright © 2018 Elsevier Ltd. All rights reserved.

The role of future scenarios to understand deep uncertainty for air quality management.

EPA Science Inventory

The environment and its interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt systemdynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challeng...

Different Visual Preference Patterns in Response to Simple and Complex Dynamic Social Stimuli in Preschool-Aged Children with Autism Spectrum Disorders

PubMed Central

Shi, Lijuan; Zhou, Yuanyue; Ou, Jianjun; Gong, Jingbo; Wang, Suhong; Cui, Xilong; Lyu, Hailong; Zhao, Jingping; Luo, Xuerong

2015-01-01

Eye-tracking studies in young children with autism spectrum disorder (ASD) have shown a visual attention preference for geometric patterns when viewing paired dynamic social images (DSIs) and dynamic geometric images (DGIs). In the present study, eye-tracking of two different paired presentations of DSIs and DGIs was monitored in a group of 13 children aged 4 to 6 years with ASD and 20 chronologically age-matched typically developing children (TDC). The results indicated that compared with the control group, children with ASD attended significantly less to DSIs showing two or more children playing than to similar DSIs showing a single child. Visual attention preference in 4- to 6-year-old children with ASDs, therefore, appears to be modulated by the type of visual stimuli. PMID:25781170

The Socially Situated Dynamics of Children's Learning Processes in Classrooms: What Do We Learn from a Complex Dynamic Systems Approach?

ERIC Educational Resources Information Center

Steenbeek, Henderien; van Vondel, Sabine; van Geert, Paul

2017-01-01

This article concentrates on the question what kind of model--conceptual and statistical--can serve as a good working model for the study of learning and teaching processes qua processes. We claim that a good way of answering this question is to begin by observing a teaching and learning process as, where, and when it occurs. In addition, a…

Dynamic Creation of Social Networks for Syndromic Surveillance Using Information Fusion

NASA Astrophysics Data System (ADS)

Holsopple, Jared; Yang, Shanchieh; Sudit, Moises; Stotz, Adam

To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.

The Emergence of Temporal Structures in Dynamical Systems

NASA Astrophysics Data System (ADS)

Mainzer, Klaus

2010-10-01

Dynamical systems in classical, relativistic and quantum physics are ruled by laws with time reversibility. Complex dynamical systems with time-irreversibility are known from thermodynamics, biological evolution, growth of organisms, brain research, aging of people, and historical processes in social sciences. Complex systems are systems that compromise many interacting parts with the ability to generate a new quality of macroscopic collective behavior the manifestations of which are the spontaneous emergence of distinctive temporal, spatial or functional structures. But, emergence is no mystery. In a general meaning, the emergence of macroscopic features results from the nonlinear interactions of the elements in a complex system. Mathematically, the emergence of irreversible structures is modelled by phase transitions in non-equilibrium dynamics of complex systems. These methods have been modified even for chemical, biological, economic and societal applications (e.g., econophysics). Emergence of irreversible structures can also be simulated by computational systems. The question arises how the emergence of irreversible structures is compatible with the reversibility of fundamental physical laws. It is argued that, according to quantum cosmology, cosmic evolution leads from symmetry to complexity of irreversible structures by symmetry breaking and phase transitions. Thus, arrows of time and aging processes are not only subjective experiences or even contradictions to natural laws, but they can be explained by quantum cosmology and the nonlinear dynamics of complex systems. Human experiences and religious concepts of arrows of time are considered in a modern scientific framework. Platonic ideas of eternity are at least understandable with respect to mathematical invariance and symmetry of physical laws. Heraclit’s world of change and dynamics can be mapped onto our daily real-life experiences of arrows of time.

Predation Risk Shapes Social Networks in Fission-Fusion Populations

PubMed Central

Kelley, Jennifer L.; Morrell, Lesley J.; Inskip, Chloe; Krause, Jens; Croft, Darren P.

2011-01-01

Predation risk is often associated with group formation in prey, but recent advances in methods for analysing the social structure of animal societies make it possible to quantify the effects of risk on the complex dynamics of spatial and temporal organisation. In this paper we use social network analysis to investigate the impact of variation in predation risk on the social structure of guppy shoals and the frequency and duration of shoal splitting (fission) and merging (fusion) events. Our analyses revealed that variation in the level of predation risk was associated with divergent social dynamics, with fish in high-risk populations displaying a greater number of associations with overall greater strength and connectedness than those from low-risk sites. Temporal patterns of organisation also differed according to predation risk, with fission events more likely to occur over two short time periods (5 minutes and 20 minutes) in low-predation fish and over longer time scales (>1.5 hours) in high-predation fish. Our findings suggest that predation risk influences the fine-scale social structure of prey populations and that the temporal aspects of organisation play a key role in defining social systems. PMID:21912627

Cortical responses to dynamic emotional facial expressions generalize across stimuli, and are sensitive to task-relevance, in adults with and without Autism.

PubMed

Kliemann, Dorit; Richardson, Hilary; Anzellotti, Stefano; Ayyash, Dima; Haskins, Amanda J; Gabrieli, John D E; Saxe, Rebecca R

2018-06-01

Individuals with Autism Spectrum Disorders (ASD) report difficulties extracting meaningful information from dynamic and complex social cues, like facial expressions. The nature and mechanisms of these difficulties remain unclear. Here we tested whether that difficulty can be traced to the pattern of activity in "social brain" regions, when viewing dynamic facial expressions. In two studies, adult participants (male and female) watched brief videos of a range of positive and negative facial expressions, while undergoing functional magnetic resonance imaging (Study 1: ASD n = 16, control n = 21; Study 2: ASD n = 22, control n = 30). Patterns of hemodynamic activity differentiated among facial emotional expressions in left and right superior temporal sulcus, fusiform gyrus, and parts of medial prefrontal cortex. In both control participants and high-functioning individuals with ASD, we observed (i) similar responses to emotional valence that generalized across facial expressions and animated social events; (ii) similar flexibility of responses to emotional valence, when manipulating the task-relevance of perceived emotions; and (iii) similar responses to a range of emotions within valence. Altogether, the data indicate that there was little or no group difference in cortical responses to isolated dynamic emotional facial expressions, as measured with fMRI. Difficulties with real-world social communication and social interaction in ASD may instead reflect differences in initiating and maintaining contingent interactions, or in integrating social information over time or context. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression.

PubMed

So, Nina; Franks, Becca; Lim, Sean; Curley, James P

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David's Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg's Hub Centrality and Bonacich's Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive behavioral characterization of group-living animals with the utilization of novel statistical methods to further our understanding of the neurobiological basis of social behavior at the individual, relationship and group levels.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression

PubMed Central

So, Nina; Franks, Becca; Lim, Sean; Curley, James P.

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David’s Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg’s Hub Centrality and Bonacich’s Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive behavioral characterization of group-living animals with the utilization of novel statistical methods to further our understanding of the neurobiological basis of social behavior at the individual, relationship and group levels. PMID:26226265

Role of future scenarios in understanding deep uncertainty in long-term air quality management

EPA Science Inventory

The environment and its interactions with human systems, whether economic, social or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of deep uncertainty presents a challenge to ...

Scaling up complexity in host-pathogens interaction models. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Aguiar, Maíra

2015-12-01

Caused by micro-organisms that are pathogenic to the host, infectious diseases have caused debilitation and premature death to large portions of the human population, leading to serious social-economic concerns. The persistence and increase in the occurrence of infectious diseases as well the emergence or resurgence of vector-borne diseases are closely related with demographic factors such as the uncontrolled urbanization and remarkable population growth, political, social and economical changes, deforestation, development of resistance to insecticides and drugs and increased human travel. In recent years, mathematical modeling became an important tool for the understanding of infectious disease epidemiology and dynamics, addressing ideas about the components of host-pathogen interactions. Acting as a possible tool to understand, predict the spread of infectious diseases these models are also used to evaluate the introduction of intervention strategies like vector control and vaccination. Many scientific papers have been published recently on these topics, and most of the models developed try to incorporate factors focusing on several different aspects of the disease (and eventually biological aspects of the vector), which can imply rich dynamic behavior even in the most basic dynamical models. As one example to be cited, there is a minimalistic dengue model that has shown rich dynamic structures, with bifurcations (Hopf, pitchfork, torus and tangent bifurcations) up to chaotic attractors in unexpected parameter regions [1,2], which was able to describe the large fluctuations observed in empirical outbreak data [3,4].

Contact structure, mobility, environmental impact and behaviour: the importance of social forces to infectious disease dynamics and disease ecology.

PubMed

Arthur, Ronan F; Gurley, Emily S; Salje, Henrik; Bloomfield, Laura S P; Jones, James H

2017-05-05

Human factors, including contact structure, movement, impact on the environment and patterns of behaviour, can have significant influence on the emergence of novel infectious diseases and the transmission and amplification of established ones. As anthropogenic climate change alters natural systems and global economic forces drive land-use and land-cover change, it becomes increasingly important to understand both the ecological and social factors that impact infectious disease outcomes for human populations. While the field of disease ecology explicitly studies the ecological aspects of infectious disease transmission, the effects of the social context on zoonotic pathogen spillover and subsequent human-to-human transmission are comparatively neglected in the literature. The social sciences encompass a variety of disciplines and frameworks for understanding infectious diseases; however, here we focus on four primary areas of social systems that quantitatively and qualitatively contribute to infectious diseases as social-ecological systems. These areas are social mixing and structure, space and mobility, geography and environmental impact, and behaviour and behaviour change. Incorporation of these social factors requires empirical studies for parametrization, phenomena characterization and integrated theoretical modelling of social-ecological interactions. The social-ecological system that dictates infectious disease dynamics is a complex system rich in interacting variables with dynamically significant heterogeneous properties. Future discussions about infectious disease spillover and transmission in human populations need to address the social context that affects particular disease systems by identifying and measuring qualitatively important drivers.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'. © 2017 The Author(s).

Multilevel dynamic systems affecting introduction of HIV/STI prevention innovations among Chinese women in sex work establishments.

PubMed

Weeks, Margaret R; Li, Jianghong; Liao, Susu; Zhang, Qingning; Dunn, Jennifer; Wang, Yanhong; Jiang, Jingmei

2013-10-01

Social and public health scientists are increasingly interested in applying system dynamics theory to improve understanding and to harness the forces of change within complex, multilevel systems that affect community intervention implementation, effects, and sustainability. Building a system dynamics model based on ethnographic case study has the advantage of using empirically documented contextual factors and processes of change in a real-world and real-time setting that can then be tested in the same and other settings. System dynamics modeling offers great promise for addressing persistent problems like HIV and other sexually transmitted epidemics, particularly in complex rapidly developing countries such as China. We generated a system dynamics model of a multilevel intervention we conducted to promote female condoms for HIV/sexually transmitted infection (STI) prevention among Chinese women in sex work establishments. The model reflects factors and forces affecting the study's intervention, implementation, and effects. To build this conceptual model, we drew on our experiences and findings from this intensive, longitudinal mixed-ethnographic and quantitative four-town comparative case study (2007-2012) of the sex work establishments, the intervention conducted in them, and factors likely to explain variation in process and outcomes in the four towns. Multiple feedback loops in the sex work establishments, women's social networks, and the health organization responsible for implementing HIV/STI interventions in each town and at the town level directly or indirectly influenced the female condom intervention. We present the conceptual system dynamics model and discuss how further testing in this and other settings can inform future community interventions to reduce HIV and STIs.

Multilevel Dynamic Systems Affecting Introduction of HIV/STI Prevention Innovations among Chinese Women in Sex-work Establishments

PubMed Central

Weeks, Margaret R.; Li, Jianghong; Liao, Susu; Zhang, Qingning; Dunn, Jennifer; Wang, Yanhong; Jiang, Jingmei

2015-01-01

Social and public health scientists are increasingly interested in applying system dynamics theory to improve understanding and to harness the forces of change within complex, multilevel systems that affect community intervention implementation, effects, and sustainability. Building a system dynamics model based on ethnographic case study has the advantage of using empirically documented contextual factors and processes of change in a real world and real time setting that can then be tested in the same and other settings. System dynamics modeling offers great promise for addressing persistent problems like HIV and other sexually transmitted epidemics, particularly in complex rapidly developing countries like China. We generated a system dynamics model of a multilevel intervention we conducted to promote female condoms (FC) for HIV/STI prevention among Chinese women in sex-work establishments. The model reflects factors and forces affecting the study’s intervention implementation and effects. To build this conceptual model, we drew on our experiences and findings from this intensive, longitudinal mixed ethnographic and quantitative four-town comparative case study (2007–2012) of the sex-work establishments, the intervention conducted in them, and factors likely to explain variation in process and outcomes in the four towns. Multiple feedback loops in the sex-work establishments, women’s social networks, and the health organization responsible for implementing HIV/STI interventions in each town and at the town level directly or indirectly influenced the FC intervention. We present the conceptual system dynamics model and discuss how further testing in this and other settings can inform future community interventions to reduce HIV and STIs. PMID:24084394

Perspective of Islamic Self: Rethinking Ibn al-Qayyim's Three-Heart Model from the Scope of Dynamical Social Psychology.

PubMed

Briki, Walid; Amara, Mahfoud

2018-06-01

The present article proposes the perspective of Islamic self (PIS), which is guided by three core principles. First, the Islamic self is shaped by the God's predicament: The life test. Second, the structure of the self and its spiritual virtues represent means to succeed the life test. Third, the complex dynamics of the self can be mathematically formalized into a parsimonious framework. Specifically, the PIS considers the self as a dynamical system characterized by the emergence of self-organized stable and unstable patterns taking the form of positive ("illuminating heart") or negative ("darkened heart") dynamics.

Etoile Project : Social Intelligent ICT-System for very large scale education in complex systems

NASA Astrophysics Data System (ADS)

Bourgine, P.; Johnson, J.

2009-04-01

The project will devise new theory and implement new ICT-based methods of delivering high-quality low-cost postgraduate education to many thousands of people in a scalable way, with the cost of each extra student being negligible (< a few Euros). The research will create an in vivo laboratory of one to ten thousand postgraduate students studying courses in complex systems. This community is chosen because it is large and interdisciplinary and there is a known requirement for courses for thousand of students across Europe. The project involves every aspect of course production and delivery. Within this the research focused on the creation of a Socially Intelligent Resource Mining system to gather large volumes of high quality educational resources from the internet; new methods to deconstruct these to produce a semantically tagged Learning Object Database; a Living Course Ecology to support the creation and maintenance of evolving course materials; systems to deliver courses; and a ‘socially intelligent assessment system'. The system will be tested on one to ten thousand postgraduate students in Europe working towards the Complex System Society's title of European PhD in Complex Systems. Étoile will have a very high impact both scientifically and socially by (i) the provision of new scalable ICT-based methods for providing very low cost scientific education, (ii) the creation of new mathematical and statistical theory for the multiscale dynamics of complex systems, (iii) the provision of a working example of adaptation and emergence in complex socio-technical systems, and (iv) making a major educational contribution to European complex systems science and its applications.

Theory of rumour spreading in complex social networks

NASA Astrophysics Data System (ADS)

Nekovee, M.; Moreno, Y.; Bianconi, G.; Marsili, M.

2007-01-01

We introduce a general stochastic model for the spread of rumours, and derive mean-field equations that describe the dynamics of the model on complex social networks (in particular, those mediated by the Internet). We use analytical and numerical solutions of these equations to examine the threshold behaviour and dynamics of the model on several models of such networks: random graphs, uncorrelated scale-free networks and scale-free networks with assortative degree correlations. We show that in both homogeneous networks and random graphs the model exhibits a critical threshold in the rumour spreading rate below which a rumour cannot propagate in the system. In the case of scale-free networks, on the other hand, this threshold becomes vanishingly small in the limit of infinite system size. We find that the initial rate at which a rumour spreads is much higher in scale-free networks than in random graphs, and that the rate at which the spreading proceeds on scale-free networks is further increased when assortative degree correlations are introduced. The impact of degree correlations on the final fraction of nodes that ever hears a rumour, however, depends on the interplay between network topology and the rumour spreading rate. Our results show that scale-free social networks are prone to the spreading of rumours, just as they are to the spreading of infections. They are relevant to the spreading dynamics of chain emails, viral advertising and large-scale information dissemination algorithms on the Internet.

Public health impact of disease-behavior dynamics. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Wells, Chad R.; Galvani, Alison P.

2015-12-01

In a loop of dynamic feedback, behavior such as the decision to vaccinate, hand washing, or avoidance influences the progression of the epidemic, yet behavior is driven by the individual's and population's perceived risk of infection during an outbreak. In what we believe will become a seminal paper that stimulates future research as well as an informative teaching aid, Wang et. al. comprehensively review methodological advances that have been used to incorporate human behavior into epidemiological models on the effects of coupling disease transmission and behavior on complex social networks [1]. As illustrated by the recent outbreaks of measles and Middle Eastern Respiratory Syndrome (MERS), here we highlight the importance of coupling behavior and disease transmission that Wang et al. address.

New Communitarianism Movements and Complex Utopia

NASA Astrophysics Data System (ADS)

Akdeniz, K. Gediz

Simulation is a rapidly growing field in social sciences. Simulation theories in social sciences are considered to critique social dynamics and societies which are mostly simulated by media, cinema, TV, internet, etc. Recently we (Akdeniz KG, Disorder in complex human system. In: Fritzsch H, Phua KK (eds) Singapore: proceedings of the conference in Honour of Murray Gell-Mann's 80th birthday quantum mechanics, elementary particles, quantum cosmology and complexity. World Scientific Publishing, Hackensack, pp 630-637, 2009) purposed a simulation theory as a critique theory to investigate disordered human behaviors. In this theory, "Disorder-Sensitive Human Behaviors (DSHB) Simulation Theory", chaotic awareness is also considered as a reality principle in simulation world to complete Baudrillard Simulation Theory (Baudrillard J, Simulacra and simulation. University of Michigan Press, Michigan, 1995). We call the emergence of this reality as zuhur which is different than simulacra. More recently we proposed the complex utopia (Akdeniz KG, From Simulacra to Zuhur in Complex Utopia. 11th International Conference of the Utopian Studies Society, Lublin, 2010; Akdeniz KG, The new identities of the physicist: cyborg-physicist and post-physicist. In: Proceedings of the conference of world international conference of technology and education, Beirut, 2010) to critique the complex societies and communities in simulation world. The challenging agents in the complex utopia are both simulacra and zuhur. In this paper we would like to review "What is the complex utopia?" And we shall critique some global events in framework of complex utopia with particular examples in socio-economic and political contexts.

Self-feedbacks determine the sustainability of human interventions in eco-social complex systems: Impacts on biodiversity and ecosystem health

PubMed Central

Ortiz, Marco

2017-01-01

Several administrative polices have been implemented in order to reduce the negative impacts of fishing on natural ecosystems. Four eco-social models with different levels of complexity were constructed, which represent the seaweed harvest in central-northern Chile under two different regimes, Management and Exploitation Areas for Benthic Resources (MAEBRs) and Open Access Areas (OAAs). The dynamics of both regimes were analyzed using the following theoretical frameworks: (1) Loop Analysis, which allows the local stability or sustainability of the models and scenarios to be assessed; and (2) Hessian´s optimization procedure of a global fishery function (GFF) that represents each dynamics of each harvest. The results suggest that the current fishing dynamics in MAEBRs are not sustainable unless the market demand presents some type of control (i.e. taxes). Further, the results indicated that if the demand changes to a self-negative feedback (self-control) in MAEBRs, the stability is increased and, simultaneously, a relative maximum for the GFF is reached. Contrarily, the sustainability of the model/system representing the harvest (principally by cutting plants) in OAAs is not reached. The implementation of an “ecological” tax for intensive artisanal fisheries with low operational cost is proposed. The network analysis developed here is proposed as a general strategy for studying the effects of human interventions in marine coastal ecosystems under transient (short-term) dynamics. PMID:28453548

Self-feedbacks determine the sustainability of human interventions in eco-social complex systems: Impacts on biodiversity and ecosystem health.

PubMed

Ortiz, Marco; Levins, Richard

2017-01-01

Several administrative polices have been implemented in order to reduce the negative impacts of fishing on natural ecosystems. Four eco-social models with different levels of complexity were constructed, which represent the seaweed harvest in central-northern Chile under two different regimes, Management and Exploitation Areas for Benthic Resources (MAEBRs) and Open Access Areas (OAAs). The dynamics of both regimes were analyzed using the following theoretical frameworks: (1) Loop Analysis, which allows the local stability or sustainability of the models and scenarios to be assessed; and (2) Hessian´s optimization procedure of a global fishery function (GFF) that represents each dynamics of each harvest. The results suggest that the current fishing dynamics in MAEBRs are not sustainable unless the market demand presents some type of control (i.e. taxes). Further, the results indicated that if the demand changes to a self-negative feedback (self-control) in MAEBRs, the stability is increased and, simultaneously, a relative maximum for the GFF is reached. Contrarily, the sustainability of the model/system representing the harvest (principally by cutting plants) in OAAs is not reached. The implementation of an "ecological" tax for intensive artisanal fisheries with low operational cost is proposed. The network analysis developed here is proposed as a general strategy for studying the effects of human interventions in marine coastal ecosystems under transient (short-term) dynamics.

Catalan in the Twenty-First Century

ERIC Educational Resources Information Center

Urla, Jacqueline

2013-01-01

This special issue devoted to Catalonia--one of the most successful and longstanding language movements in Europe--gives a unique opportunity to understand some of the complex social dynamics engendered as language revival unfolds and to appreciate the value of in-depth interviewing, focus groups, and ethnographic work in making sometimes subtle…

Saving Face: Managing Rapport in a Problem-Based Learning Group

ERIC Educational Resources Information Center

Robinson, Leslie; Harris, Ann; Burton, Rob

2015-01-01

This qualitative study investigated the complex social aspects of communication required for students to participate effectively in Problem-Based Learning and explored how these dynamics are managed. The longitudinal study of a group of first-year undergraduates examined interactions using Rapport Management as a framework to analyse communication…

Resilience thinking: integrating resilience, adaptability and transformability

Treesearch

Carl Folke; Stephen R. Carpenter; Brian Walker; Marten Scheffer; Terry Chapin; Johan Rockstrom

2010-01-01

Resilience thinking addresses the dynamics and development of complex social-ecological systems (SES). Three aspects are central: resilience, adaptability and transformability. These aspects interrelate across multiple scales. Resilience in this context is the capacity of a SES to continually change and adapt yet remain within critical thresholds. Adaptability is part...

Cultivating Critical Reflection: Educators Making Sense and Meaning of Professional Identity and Relational Dynamics in Complex Practice

ERIC Educational Resources Information Center

Morgan, Ann

2017-01-01

Critical reflection underpins socially just and inclusive practices that are distinguishing features of democratic learning communities. Critical reflection supports educators' interrogation of the underlying assumptions, intentions, values and beliefs that shape their worldview and sociocultural standpoint. Dominant sociocultural norms…

Emerging Action Research Traditions: Rigor in Practice

ERIC Educational Resources Information Center

Watkins, Karen E.; Nicolaides, Aliki; Marsick, Victoria J.

2016-01-01

The authors argue here that contemporary use of action research shares the exploratory, inductive nature of many qualitative research approaches--no matter the type of data collected--because the type of research problems studied are set in complex, dynamic, rapidly changing contexts and because action research is undertaken to support social and…

Individuals and Leadership in an Australian Secondary Science Department: A Qualitative Study

ERIC Educational Resources Information Center

Melville, Wayne; Wallace, John; Bartley, Anthony

2007-01-01

In this article, we consider the complex and dynamic inter-relationships between individual science teachers, the social space of their work and their dispositions towards teacher leadership. Research into the representation of school science departments through individual science teachers is scarce. We explore the representations of four…

Narrative dynamics in social groups: A discrete choice model

NASA Astrophysics Data System (ADS)

Antoci, A.; Bellanca, N.; Galdi, G.; Sodini, M.

2018-05-01

Individuals follow different rules for action: they react swiftly, grasping the short-term advantages in sight, or they waste cognitive resources to complete otherwise easy tasks, but they are able to plan ahead future complex decisions. Scholars from different disciplines studied the conditions under which either decision rule may enhance the fitness of its adopters, with a focus on the environmental features. However, we here propose that a crucial feature of the evolution of populations and their decision rules is rather inter-group interactions. Indeed, we study what happens when two groups support different decision rules, encapsulated in narratives, and their populations interact with each other. In particular, we assume that the payoff of each rule depends on the share of both social groups which adopt such rules. We then describe the most salient dynamics scenarios and identify the conditions which lead to chaotic dynamics and multistability regimes.

Non-communicable diseases in Indian slums: re-framing the Social Determinants of Health.

PubMed

Lumagbas, Lily Beth; Coleman, Harry Laurence Selby; Bunders, Joske; Pariente, Antoine; Belonje, Anne; de Cock Buning, Tjard

2018-01-01

The epidemic of non-communicable diseases (NCDs) in slums has pushed its residents to heightened vulnerability. The Social Determinants of Health (SDH) framework has been used to understand the social dynamics and impact of NCDs, especially in poorly resourced communities. Whilst the SDH has helped to discredit the characterisation of NCDs as diseases of affluence, its impact on policy has been less definite. Given the multitude of factors that interact in the presentation of NCDs, operationalising the SDH for policies and programmes that account for the contextual complexity of slums has stalled. To organise the complex networks of relations between SDH in slums so as to identify options for Indian municipal policy that are feasible to implement in the short term. The study reviews the literature describing SDH in Indian slums, specifically those that establish causal relations between SDH and NCDs. Root cause analysis was then used to organise the identified relations of SDH and NCDs. Although poverty remains the largest structural determinant of health in slums, the multi-dimensional relations between SDH and NCDs are structured around four themes that describe the dynamics of slums, namely scarce clean water, low education, physical (in)activity and transportation. From the reviewed literature, four logic trees visualising the relations between SDH in slums and NCDs were constructed. The logic trees separate symptomatic problems from their more distal causes, and recommendations were formulated based on features of these relationships that are amenable to policy intervention. Root cause analysis provides a means to focus the lens of examination of SDH, as evidenced here for Indian slums. It provides a guide for the development of policies that are grounded in the actual health concerns of people in slums, and takes account of the complex pathways through which diseases are socially constituted.

How Random Is Social Behaviour? Disentangling Social Complexity through the Study of a Wild House Mouse Population

PubMed Central

Perony, Nicolas; Tessone, Claudio J.; König, Barbara; Schweitzer, Frank

2012-01-01

Out of all the complex phenomena displayed in the behaviour of animal groups, many are thought to be emergent properties of rather simple decisions at the individual level. Some of these phenomena may also be explained by random processes only. Here we investigate to what extent the interaction dynamics of a population of wild house mice (Mus domesticus) in their natural environment can be explained by a simple stochastic model. We first introduce the notion of perceptual landscape, a novel tool used here to describe the utilisation of space by the mouse colony based on the sampling of individuals in discrete locations. We then implement the behavioural assumptions of the perceptual landscape in a multi-agent simulation to verify their accuracy in the reproduction of observed social patterns. We find that many high-level features – with the exception of territoriality – of our behavioural dataset can be accounted for at the population level through the use of this simplified representation. Our findings underline the potential importance of random factors in the apparent complexity of the mice's social structure. These results resonate in the general context of adaptive behaviour versus elementary environmental interactions. PMID:23209394

Cooperation dynamics of generalized reciprocity in state-based social dilemmas

NASA Astrophysics Data System (ADS)

Stojkoski, Viktor; Utkovski, Zoran; Basnarkov, Lasko; Kocarev, Ljupco

2018-05-01

We introduce a framework for studying social dilemmas in networked societies where individuals follow a simple state-based behavioral mechanism based on generalized reciprocity, which is rooted in the principle "help anyone if helped by someone." Within this general framework, which applies to a wide range of social dilemmas including, among others, public goods, donation, and snowdrift games, we study the cooperation dynamics on a variety of complex network examples. By interpreting the studied model through the lenses of nonlinear dynamical systems, we show that cooperation through generalized reciprocity always emerges as the unique attractor in which the overall level of cooperation is maximized, while simultaneously exploitation of the participating individuals is prevented. The analysis elucidates the role of the network structure, here captured by a local centrality measure which uniquely quantifies the propensity of the network structure to cooperation by dictating the degree of cooperation displayed both at the microscopic and macroscopic level. We demonstrate the applicability of the analysis on a practical example by considering an interaction structure that couples a donation process with a public goods game.

Contact structure, mobility, environmental impact and behaviour: the importance of social forces to infectious disease dynamics and disease ecology

PubMed Central

Gurley, Emily S.

2017-01-01

Human factors, including contact structure, movement, impact on the environment and patterns of behaviour, can have significant influence on the emergence of novel infectious diseases and the transmission and amplification of established ones. As anthropogenic climate change alters natural systems and global economic forces drive land-use and land-cover change, it becomes increasingly important to understand both the ecological and social factors that impact infectious disease outcomes for human populations. While the field of disease ecology explicitly studies the ecological aspects of infectious disease transmission, the effects of the social context on zoonotic pathogen spillover and subsequent human-to-human transmission are comparatively neglected in the literature. The social sciences encompass a variety of disciplines and frameworks for understanding infectious diseases; however, here we focus on four primary areas of social systems that quantitatively and qualitatively contribute to infectious diseases as social–ecological systems. These areas are social mixing and structure, space and mobility, geography and environmental impact, and behaviour and behaviour change. Incorporation of these social factors requires empirical studies for parametrization, phenomena characterization and integrated theoretical modelling of social–ecological interactions. The social–ecological system that dictates infectious disease dynamics is a complex system rich in interacting variables with dynamically significant heterogeneous properties. Future discussions about infectious disease spillover and transmission in human populations need to address the social context that affects particular disease systems by identifying and measuring qualitatively important drivers. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289265

Multiobjective Optimal Control Methodology for the Analysis of Certain Sociodynamic Problems

DTIC Science & Technology

2009-03-01

but less expensive in both time and memory. 137 References [1] R. Albert and A-L Barabasi. Statistical mechanics of complex networks. Reviews of Modern...Review, E(51):4282–4286, 1995. [24] D. Helbing, P. Molnar, and F. Schweitzer . Computer simulation of pedestrian dynamics and trail formation. May 1998...Patterson AFB, OH, 2001. [49] F. Schweitzer . Brownian Agents and Active Particles. Springer, Santa Fe, NM, 2003. [50] P. Sen. Complexities of social

Collective dynamics of social annotation

PubMed Central

Cattuto, Ciro; Barrat, Alain; Baldassarri, Andrea; Schehr, Gregory; Loreto, Vittorio

2009-01-01

The enormous increase of popularity and use of the worldwide web has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with keywords known as “tags.” Understanding the rich emergent structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks (RWs), and complex networks theory, can effectively contribute to the mathematical modeling of social annotation systems. Here, we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of RWs. This modeling framework reproduces several aspects, thus far unexplained, of social annotation, among which are the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and that are typically hard to access. PMID:19506244

The social and political lives of zoonotic disease models: narratives, science and policy.

PubMed

Leach, Melissa; Scoones, Ian

2013-07-01

Zoonotic diseases currently pose both major health threats and complex scientific and policy challenges, to which modelling is increasingly called to respond. In this article we argue that the challenges are best met by combining multiple models and modelling approaches that elucidate the various epidemiological, ecological and social processes at work. These models should not be understood as neutral science informing policy in a linear manner, but as having social and political lives: social, cultural and political norms and values that shape their development and which they carry and project. We develop and illustrate this argument in relation to the cases of H5N1 avian influenza and Ebola, exploring for each the range of modelling approaches deployed and the ways they have been co-constructed with a particular politics of policy. Addressing the complex, uncertain dynamics of zoonotic disease requires such social and political lives to be made explicit in approaches that aim at triangulation rather than integration, and plural and conditional rather than singular forms of policy advice. Copyright © 2013 Elsevier Ltd. All rights reserved.

Noise-induced polarization switching in complex networks

NASA Astrophysics Data System (ADS)

Haerter, Jan O.; Díaz-Guilera, Albert; Serrano, M. Ángeles

2017-04-01

The combination of bistability and noise is ubiquitous in complex systems, from biology to social interactions, and has important implications for their functioning and resilience. Here we use a simple three-state dynamical process, in which nodes go from one pole to another through an intermediate state, to show that noise can induce polarization switching in bistable systems if dynamical correlations are significant. In large, fully connected networks, where dynamical correlations can be neglected, increasing noise yields a collapse of bistability to an unpolarized configuration where the three possible states of the nodes are equally likely. In contrast, increased noise induces abrupt and irreversible polarization switching in sparsely connected networks. In multiplexes, where each layer can have a different polarization tendency, one layer is dominant and progressively imposes its polarization state on the other, offsetting or promoting the ability of noise to switch its polarization. Overall, we show that the interplay of noise and dynamical correlations can yield discontinuous transitions between extremes, which cannot be explained by a simple mean-field description.

An Examination of Long-Term Environmental-Social Dynamics in the Balkans

NASA Astrophysics Data System (ADS)

Kulkarni, C.; Boger, R. A.

2015-12-01

This study examines the interactions of environmental and social dynamics in Central Balkans over the past millennium, a period that experienced three major climatic phases (Medieval Climate Anomaly, Little Ice Age, and the warm 20th century). Meanwhile, the same period witnessed a complex human history with the emergence-rise-decline of the Ottoman Empire and subsequent socio-political events (e.g. wars, famines, migrations). Environmental datasets for the analysis include biological proxies (pollen, spores, and charcoal), geochemical signals through X-ray fluorescence (XRF), and a detailed chronology based on AMS 14C dating of two western and central Serbian lakes while social datasets include historic population data, land use, settlement patterns, and critical historic events derived from a review of the literature and local archives. Among the environmental datasets, indigenous tree and herbaceous pollen from these Central Balkans records demonstrate fluctuations in woodland-grassland dynamics whereas potassium and titanium counts obtained through XRF act as a proxy for surface erosion and clastic input into the lakes. Microscopic charcoal, cereal pollen and subordinate anthropogenic pollen (e.g. cultivated fruits and vegetables) are used to distinguish strong human impact over the landscape. These key anthropogenic indicators create a more thorough social component of the analysis in association with the social datasets. After reconstructing the individual time series for each environmental and social dataset, the two Central Balkan records are correlated in order to identify the environmental and social homogeneity and heterogeneity patterns occurring at shorter and longer timescales during the period. Results provide insights on how a region responds to social and environmental stressors and our approach demonstrates ways to integrate natural and social science system research.

Noise focusing and the emergence of coherent activity in neuronal cultures

NASA Astrophysics Data System (ADS)

Orlandi, Javier G.; Soriano, Jordi; Alvarez-Lacalle, Enrique; Teller, Sara; Casademunt, Jaume

2013-09-01

At early stages of development, neuronal cultures in vitro spontaneously reach a coherent state of collective firing in a pattern of nearly periodic global bursts. Although understanding the spontaneous activity of neuronal networks is of chief importance in neuroscience, the origin and nature of that pulsation has remained elusive. By combining high-resolution calcium imaging with modelling in silico, we show that this behaviour is controlled by the propagation of waves that nucleate randomly in a set of points that is specific to each culture and is selected by a non-trivial interplay between dynamics and topology. The phenomenon is explained by the noise focusing effect--a strong spatio-temporal localization of the noise dynamics that originates in the complex structure of avalanches of spontaneous activity. Results are relevant to neuronal tissues and to complex networks with integrate-and-fire dynamics and metric correlations, for instance, in rumour spreading on social networks.

Emergence of grouping in multi-resource minority game dynamics

NASA Astrophysics Data System (ADS)

Huang, Zi-Gang; Zhang, Ji-Qiang; Dong, Jia-Qi; Huang, Liang; Lai, Ying-Cheng

2012-10-01

Complex systems arising in a modern society typically have many resources and strategies available for their dynamical evolutions. To explore quantitatively the behaviors of such systems, we propose a class of models to investigate Minority Game (MG) dynamics with multiple strategies. In particular, agents tend to choose the least used strategies based on available local information. A striking finding is the emergence of grouping states defined in terms of distinct strategies. We develop an analytic theory based on the mean-field framework to understand the ``bifurcations'' of the grouping states. The grouping phenomenon has also been identified in the Shanghai Stock-Market system, and we discuss its prevalence in other real-world systems. Our work demonstrates that complex systems obeying the MG rules can spontaneously self-organize themselves into certain divided states, and our model represents a basic and general mathematical framework to address this kind of phenomena in social, economical and political systems.

Complex traffic flow that allows as well as hampers lane-changing intrinsically contains social-dilemma structures

NASA Astrophysics Data System (ADS)

Iwamura, Yoshiro; Tanimoto, Jun

2018-02-01

To investigate an interesting question as to whether or not social dilemma structures can be found in a realistic traffic flow reproduced by a model, we built a new microscopic model in which an intentional driver may try lane-changing to go in front of other vehicles and may hamper others’ lane-changes. Our model consists of twofold parts; cellular automaton emulating a real traffic flow and evolutionary game theory to implement a driver’s decision making-process. Numerical results reveal that a social dilemma like the multi-player chicken game or prisoner’s dilemma game emerges depending on the traffic phase. This finding implies that a social dilemma, which has been investigated by applied mathematics so far, hides behind a traffic flow, which has been explored by fluid dynamics. Highlight - Complex system of traffic flow with consideration of driver’s decision making process is concerned. - A new model dovetailing cellular automaton with game theory is established. - Statistical result from numerical simulations reveals a social dilemma structure underlying traffic flow. - The social dilemma is triggered by a driver’s egocentric actions of lane-changing and hampering other’s lane-change.

Citizen social science: a methodology to facilitate and evaluate workplace learning in continuing interprofessional education.

PubMed

Dadich, Ann

2014-05-01

Workplace learning in continuing interprofessional education (CIPE) can be difficult to facilitate and evaluate, which can create a number of challenges for this type of learning. This article presents an innovative method to foster and investigate workplace learning in CIPE - citizen social science. Citizen social science involves clinicians as co-researchers in the systematic examination of social phenomena. When facilitated by an open-source online social networking platform, clinicians can participate via computer, smartphone, or tablet in ways that suit their needs and preferences. Furthermore, as co-researchers they can help to reveal the dynamic interplay that facilitates workplace learning in CIPE. Although yet to be tested, citizen social science offers four potential benefits: it recognises and accommodates the complexity of workplace learning in CIPE; it has the capacity to both foster and evaluate the phenomena; it can be used in situ, capturing and having direct relevance to the complexity of the workplace; and by advancing both theoretical and methodological debates on CIPE, it may reveal opportunities to improve and sustain workplace learning. By describing an example situated in the youth health sector, this article demonstrates how these benefits might be realised.

The diminishing role of hubs in dynamical processes on complex networks.

PubMed

Quax, Rick; Apolloni, Andrea; Sloot, Peter M A

2013-11-06

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein-protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature.

Integrating the social sciences to understand human-water dynamics

NASA Astrophysics Data System (ADS)

Carr, G.; Kuil, L., Jr.

2017-12-01

Many interesting and exciting socio-hydrological models have been developed in recent years. Such models often aim to capture the dynamic interplay between people and water for a variety of hydrological settings. As such, peoples' behaviours and decisions are brought into the models as drivers of and/or respondents to the hydrological system. To develop and run such models over a sufficiently long time duration to observe how the water-human system evolves the human component is often simplified according to one or two key behaviours, characteristics or decisions (e.g. a decision to move away from a drought or flood area; a decision to pump groundwater, or a decision to plant a less water demanding crop). To simplify the social component, socio-hydrological modellers often pull knowledge and understanding from existing social science theories. This requires them to negotiate complex territory, where social theories may be underdeveloped, contested, dynamically evolving, or case specific and difficult to generalise or upscale. A key question is therefore, how can this process be supported so that the resulting socio-hydrological models adequately describe the system and lead to meaningful understanding of how and why it behaves as it does? Collaborative interdisciplinary research teams that bring together social and natural scientists are likely to be critical. Joint development of the model framework requires specific attention to clarification to expose all underlying assumptions, constructive discussion and negotiation to reach agreement on the modelled system and its boundaries. Mutual benefits to social scientists can be highlighted, i.e. socio-hydrological work can provide insights for further exploring and testing social theories. Collaborative work will also help ensure underlying social theory is made explicit, and may identify ways to include and compare multiple theories. As socio-hydrology progresses towards supporting policy development, approaches that brings in stakeholders and non-scientist participants to develop the conceptual modelling framework will become essential. They are also critical for fully understanding human-water dynamics.

Dynamical analogy between economical crisis and earthquake dynamics within the nonextensive statistical mechanics framework

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Zitis, Pavlos I.; Eftaxias, Konstantinos

2013-07-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up with these different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes). We show that the populations of: (i) fracto-electromagnetic events rooted in the activation of a single fault, emerging prior to a significant earthquake, (ii) the trade volume events of different shares/economic indices, prior to a collapse, and (iii) the price fluctuation (considered as the difference of maximum minus minimum price within a day) events of different shares/economic indices, prior to a collapse, follow both the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar parameter values. The obtained results imply the existence of a dynamic analogy between earthquakes and economic crises, which moreover follow the dynamics of seizures, magnetic storms and solar flares.

Reclaiming the person: intersectionality and dynamic social categories through a psychological lens.

PubMed

Frazier, Kathryn E

2012-09-01

Psychology's conventionally treatment of individuals' engagement with and resistance to the societal processes in which they are embedded has come under scrutiny amid the rise of postmodernist and critical feminist perspectives (among many others) in the social sciences. A sample of social psychology's responses to these critiques is presented in the recently published book, Social Categories in Everyday Experience edited by Shaun Wiley et al. (2011). In this essay, the challenges of seriously addressing the critiques of psychology's conventional treatment of social categories, which implicate fundamental assumptions of the discipline, are discussed. Further, it is argued that in order to effectively construct psychological accounts of political activism and social change amid theories that are increasingly cognizant of the complexities and contingencies of social embeddiness, the person must be reclaimed and revisioned. Notions of agency that complement an intersectional and systemic vision of the social world are discussed.

The historical dynamics of social-ecological traps.

PubMed

Boonstra, Wiebren J; de Boer, Florianne W

2014-04-01

Environmental degradation is a typical unintended outcome of collective human behavior. Hardin's metaphor of the "tragedy of the commons" has become a conceived wisdom that captures the social dynamics leading to environmental degradation. Recently, "traps" has gained currency as an alternative concept to explain the rigidity of social and ecological processes that produce environmental degradation and livelihood impoverishment. The trap metaphor is, however, a great deal more complex compared to Hardin's insight. This paper takes stock of studies using the trap metaphor. It argues that the concept includes time and history in the analysis, but only as background conditions and not as a factor of causality. From a historical-sociological perspective this is remarkable since social-ecological traps are clearly path-dependent processes, which are causally produced through a conjunction of events. To prove this point the paper conceptualizes social-ecological traps as a process instead of a condition, and systematically compares history and timing in one classic and three recent studies of social-ecological traps. Based on this comparison it concludes that conjunction of social and environmental events contributes profoundly to the production of trap processes. The paper further discusses the implications of this conclusion for policy intervention and outlines how future research might generalize insights from historical-sociological studies of traps.

An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts

PubMed Central

Lade, Steven J.; Niiranen, Susa; Hentati-Sundberg, Jonas; Blenckner, Thorsten; Boonstra, Wiebren J.; Orach, Kirill; Quaas, Martin F.; Österblom, Henrik; Schlüter, Maja

2015-01-01

Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social–ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social–ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social–ecological models. PMID:26283344

Towards Understanding and Managing Sustainable Complex, Dynamic Environmental/Economic/Social Systems - The Evolving Role of the Natural Sciences

EPA Science Inventory

Historically the natural sciences have played a major role in informing environmental management decisions. However, review of landmark cases like Love Canal, NY and Times Beach, MO have shown that the value of natural science information in decision making can be overwhelmed by ...

Reducing Change Management Complexity: Aligning Change Recipient Sensemaking to Change Agent Sensegiving

ERIC Educational Resources Information Center

Kumar; Payal; Singhal, Manish

2012-01-01

Implementation of change in an organisation through culture can elicit a wide array of reactions from organisational members, spanning from acceptance to resistance. Drawing on Hatch's cultural dynamics model and on Wegner's social theory of learning, this paper dwells on an underdeveloped area in the extant literature, namely understanding change…

Quality as Sense-Making

ERIC Educational Resources Information Center

Marshall, Stephen

2016-01-01

Sense-making is a process of engaging with complex and dynamic environments that provides organisations and their leaders with a flexible and agile model of the world. The seven key properties of sense-making describe a process that is social and that respects the range of different stakeholders in an organisation. It also addresses the need to…

Reboundarying Professional Jurisdiction: Educational Work on Discount Sale

ERIC Educational Resources Information Center

Henriksson, Lea

2014-01-01

Education is a critical instrument for governments and communities managing economic and social development in global times. Reboundarying educational work reflects this dynamic where the national and local are networked in complex ways. In this frame, the focus in this article is on a policy debate on educational labour force and gendered work…

A Case for Relational Leadership and an Ethics of Care for Counteracting Bullying at Schools

ERIC Educational Resources Information Center

Smit, Brigitte; Scherman, Vanessa

2016-01-01

This paper attends to a theoretical exposition of relational leadership and ethics care as complementary approaches to educational leadership in counteracting bullying at schools. Schools constitute complex systems of activities, processes and dynamics. More specifically, a social system in schools is a web of interactions between the various…

Social Networks and Smoking: Exploring the Effects of Peer Influence and Smoker Popularity through Simulations

ERIC Educational Resources Information Center

Schaefer, David R.; adams, jimi; Haas, Steven A.

2013-01-01

Adolescent smoking and friendship networks are related in many ways that can amplify smoking prevalence. Understanding and developing interventions within such a complex system requires new analytic approaches. We draw on recent advances in dynamic network modeling to develop a technique that explores the implications of various intervention…

Supply Chain Development: Insights from Strategic Niche Management

ERIC Educational Resources Information Center

Caniels, Marjolein C. J.; Romijn, Henny A.

2008-01-01

Purpose: The purpose of this paper is to contribute to the study of supply chain design from the perspective of complex dynamic systems. Unlike extant studies that use formal simulation modelling and associated methodologies rooted in the physical sciences, it adopts a framework rooted in the social sciences, strategic niche management, which…

The Sociolinguistic Complexity of Quasi-Isolated Southern Coastal Communities.

ERIC Educational Resources Information Center

Wolfram, Walt; And Others

A sociolinguistic study of Ocracoke, an island community in North Carolina's Outer Banks, investigated the social dynamics of language change and variation. Data were gathered in interviews with 43 island residents aged 12-82, most of whose families have been on the island for several generations. Several major sociolinguistic issues were…

The "Uptake" of a Sport-for-Development Programme in South Africa

ERIC Educational Resources Information Center

Burnett, Cora

2015-01-01

This article reports on the "uptake" dynamics and resultant manifestations of a school-based, incentive-driven, sport-for-development programme in the South African context of poverty. The ecological systems theory of Brofenbrenner, the theory of complexity and a neo-liberal framework underpin the social constructions of local meanings…

The Influential Role of Sociocultural Feedbacks on Community-Managed Irrigation System Behaviors During times of Water Stress

DOE PAGES

Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.

2018-03-14

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less

The Influential Role of Sociocultural Feedbacks on Community-Managed Irrigation System Behaviors During times of Water Stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less

The Influential Role of Sociocultural Feedbacks on Community-Managed Irrigation System Behaviors During Times of Water Stress

NASA Astrophysics Data System (ADS)

Gunda, T.; Turner, B. L.; Tidwell, V. C.

2018-04-01

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. Continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.

Recent advances in mathematical criminology. Comment on "Statistical physics of crime: A review" by M.R. D'Orsogna and M. Perc

NASA Astrophysics Data System (ADS)

Rodríguez, Nancy

2015-03-01

The use of mathematical tools has long proved to be useful in gaining understanding of complex systems in physics [1]. Recently, many researchers have realized that there is an analogy between emerging phenomena in complex social systems and complex physical or biological systems [4,5,12]. This realization has particularly benefited the modeling and understanding of crime, a ubiquitous phenomena that is far from being understood. In fact, when one is interested in the bulk behavior of patterns that emerge from small and seemingly unrelated interactions as well as decisions that occur at the individual level, the mathematical tools that have been developed in statistical physics, game theory, network theory, dynamical systems, and partial differential equations can be useful in shedding light into the dynamics of these patterns [2-4,6,12].

Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

NASA Astrophysics Data System (ADS)

Gao, Zilin; Wang, Yinhe; Zhang, Lili

2018-02-01

In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

Modeling social norms and social influence in obesity

PubMed Central

Shoham, David A.; Hammond, Ross; Rahmandad, Hazhir; Wang, Youfa; Hovmand, Peter

2015-01-01

The worldwide increase in obesity has led to changes in what is considered “normal” or desirable weight, especially among populations at higher risk. We show that social norms are key to understanding the obesity epidemic, and that social influence mechanisms provide a necessary linkage between individual obesity-related behaviors and population-level characteristics. Because influence mechanisms cannot be directly observed, we show how three complex systems tools may be used to gain insights into observed epidemiologic patterns: social network analysis, agent-based modeling, and systems dynamics modeling. However, simulation and mathematical modeling approaches raise questions regarding acceptance of findings, especially among policy makers. Nevertheless, we point to modeling successes in obesity and other fields, including the NIH-funded National Collaborative on Childhood Obesity Research (NCCOR) Envison project. PMID:26576335

Interactive Social Neuroscience to Study Autism Spectrum Disorder

PubMed Central

Rolison, Max J.; Naples, Adam J.; McPartland, James C.

2015-01-01

Individuals with autism spectrum disorder (ASD) demonstrate difficulty with social interactions and relationships, but the neural mechanisms underlying these difficulties remain largely unknown. While social difficulties in ASD are most apparent in the context of interactions with other people, most neuroscience research investigating ASD have provided limited insight into the complex dynamics of these interactions. The development of novel, innovative “interactive social neuroscience” methods to study the brain in contexts with two interacting humans is a necessary advance for ASD research. Studies applying an interactive neuroscience approach to study two brains engaging with one another have revealed significant differences in neural processes during interaction compared to observation in brain regions that are implicated in the neuropathology of ASD. Interactive social neuroscience methods are crucial in clarifying the mechanisms underlying the social and communication deficits that characterize ASD. PMID:25745371

Interactive social neuroscience to study autism spectrum disorder.

PubMed

Rolison, Max J; Naples, Adam J; McPartland, James C

2015-03-01

Individuals with autism spectrum disorder (ASD) demonstrate difficulty with social interactions and relationships, but the neural mechanisms underlying these difficulties remain largely unknown. While social difficulties in ASD are most apparent in the context of interactions with other people, most neuroscience research investigating ASD have provided limited insight into the complex dynamics of these interactions. The development of novel, innovative "interactive social neuroscience" methods to study the brain in contexts with two interacting humans is a necessary advance for ASD research. Studies applying an interactive neuroscience approach to study two brains engaging with one another have revealed significant differences in neural processes during interaction compared to observation in brain regions that are implicated in the neuropathology of ASD. Interactive social neuroscience methods are crucial in clarifying the mechanisms underlying the social and communication deficits that characterize ASD.

Social regulation of emotion: messy layers

PubMed Central

Kappas, Arvid

2013-01-01

Emotions are evolved systems of intra- and interpersonal processes that are regulatory in nature, dealing mostly with issues of personal or social concern. They regulate social interaction and in extension, the social sphere. In turn, processes in the social sphere regulate emotions of individuals and groups. In other words, intrapersonal processes project in the interpersonal space, and inversely, interpersonal experiences deeply influence intrapersonal processes. Thus, I argue that the concepts of emotion generation and regulation should not be artificially separated. Similarly, interpersonal emotions should not be reduced to interacting systems of intraindividual processes. Instead, we can consider emotions at different social levels, ranging from dyads to large scale e-communities. The interaction between these levels is complex and does not only involve influences from one level to the next. In this sense the levels of emotion/regulation are messy and a challenge for empirical study. In this article, I discuss the concepts of emotions and regulation at different intra- and interpersonal levels. I extend the concept of auto-regulation of emotions (Kappas, 2008, 2011a,b) to social processes. Furthermore, I argue for the necessity of including mediated communication, particularly in cyberspace in contemporary models of emotion/regulation. Lastly, I suggest the use of concepts from systems dynamics and complex systems to tackle the challenge of the “messy layers.” PMID:23424049

Gray matter volume of the anterior insular cortex and social networking.

PubMed

Spagna, Alfredo; Dufford, Alexander J; Wu, Qiong; Wu, Tingting; Zheng, Weihao; Coons, Edgar E; Hof, Patrick R; Hu, Bin; Wu, Yanhong; Fan, Jin

2018-05-01

In human life, social context requires the engagement in complex interactions among individuals as the dynamics of social networks. The evolution of the brain as the neurological basis of the mind must be crucial in supporting social networking. Although the relationship between social networking and the amygdala, a small but core region for emotion processing, has been reported, other structures supporting sophisticated social interactions must be involved and need to be identified. In this study, we examined the relationship between morphology of the anterior insular cortex (AIC), a structure involved in basic and high-level cognition, and social networking. Two independent cohorts of individuals (New York group n = 50, Beijing group n = 100) were recruited. Structural magnetic resonance images were acquired and the social network index (SNI), a composite measure summarizing an individual's network diversity, size, and complexity, was measured. The association between morphological features of the AIC, in addition to amygdala, and the SNI was examined. Positive correlations between the measures of the volume as well as sulcal depth of the AIC and the SNI were found in both groups, while a significant positive correlation between the volume of the amygdala and the SNI was only found in the New York group. The converging results from the two groups suggest that the AIC supports network-level social interactions. © 2018 Wiley Periodicals, Inc.

Robust dynamic classes revealed by measuring the response function of a social system

PubMed Central

Crane, Riley; Sornette, Didier

2008-01-01

We study the relaxation response of a social system after endogenous and exogenous bursts of activity using the time series of daily views for nearly 5 million videos on YouTube. We find that most activity can be described accurately as a Poisson process. However, we also find hundreds of thousands of examples in which a burst of activity is followed by an ubiquitous power-law relaxation governing the timing of views. We find that these relaxation exponents cluster into three distinct classes and allow for the classification of collective human dynamics. This is consistent with an epidemic model on a social network containing two ingredients: a power-law distribution of waiting times between cause and action and an epidemic cascade of actions becoming the cause of future actions. This model is a conceptual extension of the fluctuation-dissipation theorem to social systems [Ruelle, D (2004) Phys Today 57:48–53] and [Roehner BM, et al., (2004) Int J Mod Phys C 15:809–834], and provides a unique framework for the investigation of timing in complex systems. PMID:18824681

Robust dynamic classes revealed by measuring the response function of a social system.

PubMed

Crane, Riley; Sornette, Didier

2008-10-14

We study the relaxation response of a social system after endogenous and exogenous bursts of activity using the time series of daily views for nearly 5 million videos on YouTube. We find that most activity can be described accurately as a Poisson process. However, we also find hundreds of thousands of examples in which a burst of activity is followed by an ubiquitous power-law relaxation governing the timing of views. We find that these relaxation exponents cluster into three distinct classes and allow for the classification of collective human dynamics. This is consistent with an epidemic model on a social network containing two ingredients: a power-law distribution of waiting times between cause and action and an epidemic cascade of actions becoming the cause of future actions. This model is a conceptual extension of the fluctuation-dissipation theorem to social systems [Ruelle, D (2004) Phys Today 57:48-53] and [Roehner BM, et al., (2004) Int J Mod Phys C 15:809-834], and provides a unique framework for the investigation of timing in complex systems.

Student leadership in small group science inquiry

NASA Astrophysics Data System (ADS)

Oliveira, Alandeom W.; Boz, Umit; Broadwell, George A.; Sadler, Troy D.

2014-09-01

Background: Science educators have sought to structure collaborative inquiry learning through the assignment of static group roles. This structural approach to student grouping oversimplifies the complexities of peer collaboration and overlooks the highly dynamic nature of group activity. Purpose: This study addresses this issue of oversimplification of group dynamics by examining the social leadership structures that emerge in small student groups during science inquiry. Sample: Two small student groups investigating the burning of a candle under a jar participated in this study. Design and method: We used a mixed-method research approach that combined computational discourse analysis (computational quantification of social aspects of small group discussions) with microethnography (qualitative, in-depth examination of group discussions). Results: While in one group social leadership was decentralized (i.e., students shared control over topics and tasks), the second group was dominated by a male student (centralized social leadership). Further, decentralized social leadership was found to be paralleled by higher levels of student cognitive engagement. Conclusions: It is argued that computational discourse analysis can provide science educators with a powerful means of developing pedagogical models of collaborative science learning that take into account the emergent nature of group structures and highly fluid nature of student collaboration.

The role (or not) of economic evaluation at the micro level: can Bourdieu's theory provide a way forward for clinical decision-making?

PubMed

Lessard, Chantale; Contandriopoulos, André-Pierre; Beaulieu, Marie-Dominique

2010-06-01

Despite increasing interest in health economic evaluation, investigations have shown limited use by micro (clinical) level decision-makers. A considerable amount of health decisions take place daily at the point of the clinical encounter; especially in primary care. Since every decision has an opportunity cost, ignoring economic information in family physicians' (FPs) decision-making may have a broad impact on health care efficiency. Knowledge translation of economic evaluation is often based on taken-for-granted assumptions about actors' interests and interactions, neglecting much of the complexity of social reality. Health economics literature frequently assumes a rational and linear decision-making process. Clinical decision-making is in fact a complex social, dynamic, multifaceted process, involving relationships and contextual embeddedness. FPs are embedded in complex social networks that have a significant impact on skills, attitudes, knowledge, practices, and on the information being used. Because of their socially constructed nature, understanding preferences, professional culture, practices, and knowledge translation requires serious attention to social reality. There has been little exploration by health economists of whether the problem may be more fundamental and reside in a misunderstanding of the process of decision-making. There is a need to enhance our understanding of the role of economic evaluation in decision-making from a disciplinary perspective different than health economics. This paper argues for a different conceptualization of the role of economic evaluation in FPs' decision-making, and proposes Bourdieu's sociological theory as a research framework. Bourdieu's theory of practice illustrates how the context-sensitive nature of practice must be understood as a socially constituted practical knowledge. The proposed approach could substantially contribute to a more complex understanding of the role of economic evaluation in FPs' decision-making. Copyright 2010 Elsevier Ltd. All rights reserved.

How to analytically characterize the epidemic threshold within the coupled disease-behavior systems?. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Xia, Cheng-Yi; Ding, Shuai; Sun, Shi-Wen; Wang, Li; Gao, Zhong-Ke; Wang, Juan

2015-12-01

As is well known, outbreak of epidemics may drive the human population to take some necessary measures to protect themselves from not being infected by infective ones, these precautions in turn will also keep from the further spreading of infectious diseases among the population. Thus, to fully comprehend the epidemic spreading behavior within real-world systems, the interplay between disease dynamics and human behavioral and social dynamics needs to be considered simultaneously, such that some effective containment-measures can be successfully developed [1-3].

Complex adaptive chronic care - typologies of patient journey: a case study.

PubMed

Martin, Carmel M; Grady, Deirdre; Deaconking, Susan; McMahon, Catherine; Zarabzadeh, Atieh; O'Shea, Brendan

2011-06-01

Complex adaptive chronic care (CACC) is a framework based upon complex adaptive systems' theory developed to address different stages in the patient journey in chronic illness. Simple, complicated, complex and chaotic phases are proposed as diagnostic types. To categorize phases of the patient journey and evaluate their utility as diagnostic typologies. A qualitative case study of two cohorts, identified as being at risk of avoidable hospitalization: 12 patients monitored to establish typologies, followed by 46 patients to validate the typologies. Patients were recruited from a general practitioner out-of-hours service. Self-rated health, medical and psychological health, social support, environmental concerns, medication adherence and health service use were monitored with phone calls made 3-5 times per week for an average of 4 weeks. Analysis techniques included frequency distributions, coding and categorization of patients' longitudinal data using a CACC framework. Twelve and 46 patients, mean age 69 years, were monitored for average of 28 days in cohorts 1 and 2 respectively. Cohorts 1 and 2 patient journeys were categorized as being: stable complex 66.66% vs. 67.4%, unstable complex 25% vs. 26.08% and unstable complex chaotic 8.3% vs. 6.52% respectively. An average of 0.48, 0.75 and 2 interventions per person were provided in the stable, unstable and chaotic journeys. Instability was related to complex interactions between illness, social support, environment, as well as medication and medical care issues. Longitudinal patient journeys encompass different phases with characteristic dynamics and are likely to require different interventions and strategies - thus being 'adaptive' to the changing complex dynamics of the patient's illness and care needs. CACC journey types provide a clinical tool for health professionals to focus time and care interventions in response to patterns of instability in multiple domains in chronic illness care. © 2011 Blackwell Publishing Ltd.

Consensus Emerging from the Bottom-up: the Role of Cognitive Variables in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Giardini, Francesca; Vilone, Daniele; Conte, Rosaria

2015-09-01

The study of opinions - e.g., their formation and change, and their effects on our society - by means of theoretical and numerical models has been one of the main goals of sociophysics until now, but it is one of the defining topics addressed by social psychology and complexity science. Despite the flourishing of different models and theories, several key questions still remain unanswered. The aim of this paper is to provide a cognitively grounded computational model of opinions in which they are described as mental representations and defined in terms of distinctive mental features. We also define how these representations change dynamically through different processes, describing the interplay between mental and social dynamics of opinions. We present two versions of the model, one with discrete opinions (voter model-like), and one with continuous ones (Deffuant-like). By means of numerical simulations, we compare the behaviour of our cognitive model with the classical sociophysical models, and we identify interesting differences in the dynamics of consensus for each of the models considered.

Markets on Networks

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

2003-03-01

The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

Epidemic modeling in complex realities.

PubMed

Colizza, Vittoria; Barthélemy, Marc; Barrat, Alain; Vespignani, Alessandro

2007-04-01

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

Operationalising a social-ecological system perspective on the Arctic Ocean.

PubMed

Crépin, Anne-Sophie; Gren, Åsa; Engström, Gustav; Ospina, Daniel

2017-12-01

We propose a framework to support management that builds on a social-ecological system perspective on the Arctic Ocean. We illustrate the framework's application for two policy-relevant scenarios of climate-driven change, picturing a shift in zooplankton composition and alternatively a crab invasion. We analyse archetypical system dynamics between the socio-economic, the natural, and the governance systems in these scenarios. Our holistic approach can help managers identify looming problems arising from complex system interactions and prioritise among problems and solutions, even when available data are limited.

Privilege as Privileging: Making the Dynamic and Complex Nature of Privilege and Marginalization Accessible

ERIC Educational Resources Information Center

Minarik, Joseph D.

2017-01-01

Privilege is one of the central constructs social work educators reference to increase self-awareness and concern about inequality, but it is often oversimplified. This article argues how the concept of privilege can be made more credible to learners by anchoring it to everyday business-as-usual decision making, stereotyping, and various…

Access, Status, and Representation: Some Reflections from Two Ethnographic Studies of Elite Schools

ERIC Educational Resources Information Center

Gaztambide-Fernandez, Ruben A.; Howard, Adam

2012-01-01

In this article, we use our experiences to demonstrate the limits of the "studying up" metaphor to capture the complexity of the dynamics involved in doing research on groups that occupy positions of power within social hierarchies. The article focuses on different facets of the research process, alternating between our individual narratives and a…

Approaches to incorporating climate change effects in state and transition simulation models of vegetation

Treesearch

Becky K. Kerns; Miles A. Hemstrom; David Conklin; Gabriel I. Yospin; Bart Johnson; Dominique Bachelet; Scott Bridgham

2012-01-01

Understanding landscape vegetation dynamics often involves the use of scientifically-based modeling tools that are capable of testing alternative management scenarios given complex ecological, management, and social conditions. State-and-transition simulation model (STSM) frameworks and software such as PATH and VDDT are commonly used tools that simulate how landscapes...

Explorations in Teaching Sustainable Design: A Studio Experience in Interior Design/Architecture

ERIC Educational Resources Information Center

Gurel, Meltem O.

2010-01-01

This article argues that a design studio can be a dynamic medium to explore the creative potential of the complexity of sustainability from its technological to social ends. The study seeks to determine the impact of an interior design/architecture studio experience that was initiated to teach diverse meanings of sustainability and to engage the…

Mrs. Klein and Paulo Freire: Coda for the Pain of Symbolization in the Lifeworld of the Mind

ERIC Educational Resources Information Center

Britzman, Deborah P.

2017-01-01

The preceding symposium articles speculate on the psychosocial dynamics of discrimination as reverberating with grief, mourning, melancholia, and denial. They invite a psychoanalytic paradox on the fate of inchoate loss and its complex relation to oppression and depression: constellations of attachment to loss met with its social and psychical…

Dynamic Gender Differences in a Post-Socialist Labor Market: Russia, 1991-1997

ERIC Educational Resources Information Center

Gerber, Theodore P.; Mayorova, Olga

2006-01-01

We examine how the shift from state socialism affects gender inequality in the labor market using multivariate models of employment exit, employment entry, job mobility and new job quality for 3,580 Russian adults from 1991 through 1997. Gender differences changed in a complex fashion. Relative to men, women gained greater access to employment,…

Reflective Practice on Leadership Committed to Social Justice: Counter Story of an African American Superintendent

ERIC Educational Resources Information Center

Dailey, Ardella

2015-01-01

The central assumption of this paper is that the use of autoethnography is the best approach to obtain a deeper understanding of the political context, organizational culture, and complex dynamics of a person's lived experience in a leadership position. The central narrative follows the accounts documented through systematic journaling, and…

Evidence, Expertise, and Ethics: The Making of an Influential in American Social Work

ERIC Educational Resources Information Center

Burnette, Denise

2016-01-01

The extent to which people choose their professions and professions choose their practitioners is not always clear; it is in all likelihood a "simpatico" process. But, growing attention to the study of careers can help elucidate the nexus of personal and professional forces that underpins this complex dynamic. This line of inquiry can…

Pathways to Co-Impact: Action Research and Community Organising

ERIC Educational Resources Information Center

Banks, Sarah; Herrington, Tracey; Carter, Kath

2017-01-01

This article introduces the concept of "co-impact" to characterise the complex and dynamic process of social and economic change generated by participatory action research (PAR). It argues that dominant models of research impact tend to see it as a linear process, based on a donor-recipient model, occurring at the end of a project…

The Myth of Rational Objectivity and Leadership: The Realities of a Hospital Merger from a CEO's Perspective

ERIC Educational Resources Information Center

Tobin, John H.

2009-01-01

Executive power and status depends on others' belief in the executive's capacity for control via rational decision-making, "by the numbers" and above the fray of day to day minutia. By exploring his own experience in the complex social dynamics of a long, complicated merger process--characterised by misunderstanding, incomplete…

Challenges and Experiences of Building Multidisciplinary Datasets across Cultures

NASA Astrophysics Data System (ADS)

Jamiyansharav, K.; Laituri, M.; Fernandez-Gimenez, M.; Fassnacht, S. R.; Venable, N. B. H.; Allegretti, A. M.; Reid, R.; Baival, B.; Jamsranjav, C.; Ulambayar, T.; Linn, S.; Angerer, J.

2017-12-01

Efficient data sharing and management are key challenges to multidisciplinary scientific research. These challenges are further complicated by adding a multicultural component. We address the construction of a complex database for social-ecological analysis in Mongolia. Funded by the National Science Foundation (NSF) Dynamics of Coupled Natural and Human (CNH) Systems, the Mongolian Rangelands and Resilience (MOR2) project focuses on the vulnerability of Mongolian pastoral systems to climate change and adaptive capacity. The MOR2 study spans over three years of fieldwork in 36 paired districts (Soum) from 18 provinces (Aimag) of Mongolia that covers steppe, mountain forest steppe, desert steppe and eastern steppe ecological zones. Our project team is composed of hydrologists, social scientists, geographers, and ecologists. The MOR2 database includes multiple ecological, social, meteorological, geospatial and hydrological datasets, as well as archives of original data and survey in multiple formats. Managing this complex database requires significant organizational skills, attention to detail and ability to communicate within collective team members from diverse disciplines and across multiple institutions in the US and Mongolia. We describe the database's rich content, organization, structure and complexity. We discuss lessons learned, best practices and recommendations for complex database management, sharing, and archiving in creating a cross-cultural and multi-disciplinary database.

Oxytocin and Social Motivation

PubMed Central

Gordon, Ilanit; Martin, Carina; Feldman, Ruth; Leckman, James F.

2011-01-01

Humans are fundamentally social creatures who are ‘motivated’ to be with others. In this review we examine the role of oxytocin (OT) as it relates to social motivation. OT is synthesized in the brain and throughout the body, including in the heart, thymus, gastrointestinal tract, as well as reproductive organs. The distribution of the OT receptor (OTR) system in both the brain and periphery is even more far-reaching and its expression is subject to changes over the course of development. OTR expression is also sensitive to changes in the external environment and the internal somatic world. The OT system functions as an important element within a complex, developmentally sensitive biobehavioral system. Other elements include sensory inputs, the salience, reward, and threat detection pathways, the hypothalamic-pituitary-gonadal axis, and the hypothalamic-pituitary-adrenal stress response axis. Despite an ever expanding scientific literature, key unresolved questions remain concerning the interplay of the central and peripheral components of this complex biobehavioral system that dynamically engages the brain and the body as humans interact with social partners over the course of development. PMID:21984889

Using activity theory to study cultural complexity in medical education.

PubMed

Frambach, Janneke M; Driessen, Erik W; van der Vleuten, Cees P M

2014-06-01

There is a growing need for research on culture, cultural differences and cultural effects of globalization in medical education, but these are complex phenomena to investigate. Socio-cultural activity theory seems a useful framework to study cultural complexity, because it matches current views on culture as a dynamic process situated in a social context, and has been valued in diverse fields for yielding rich understandings of complex issues and key factors involved. This paper explains how activity theory can be used in (cross-)cultural medical education research. We discuss activity theory's theoretical background and principles, and we show how these can be applied to the cultural research practice by discussing the steps involved in a cross-cultural study that we conducted, from formulating research questions to drawing conclusions. We describe how the activity system, the unit of analysis in activity theory, can serve as an organizing principle to grasp cultural complexity. We end with reflections on the theoretical and practical use of activity theory for cultural research and note that it is not a shortcut to capture cultural complexity: it is a challenge for researchers to determine the boundaries of their study and to analyze and interpret the dynamics of the activity system.

Fluctuation of similarity (FLUS) to detect transitions between distinct dynamical regimes in short time series

PubMed Central

Malik, Nishant; Marwan, Norbert; Zou, Yong; Mucha, Peter J.; Kurths, Jürgen

2016-01-01

A method to identify distinct dynamical regimes and transitions between those regimes in a short univariate time series was recently introduced [1], employing the computation of fluctuations in a measure of nonlinear similarity based on local recurrence properties. In the present work, we describe the details of the analytical relationships between this newly introduced measure and the well known concepts of attractor dimensions and Lyapunov exponents. We show that the new measure has linear dependence on the effective dimension of the attractor and it measures the variations in the sum of the Lyapunov spectrum. To illustrate the practical usefulness of the method, we identify various types of dynamical transitions in different nonlinear models. We present testbed examples for the new method’s robustness against noise and missing values in the time series. We also use this method to analyze time series of social dynamics, specifically an analysis of the U.S. crime record time series from 1975 to 1993. Using this method, we find that dynamical complexity in robberies was influenced by the unemployment rate until the late 1980’s. We have also observed a dynamical transition in homicide and robbery rates in the late 1980’s and early 1990’s, leading to increase in the dynamical complexity of these rates. PMID:25019852

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Measure of robustness for complex networks

NASA Astrophysics Data System (ADS)

Youssef, Mina Nabil

Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance (VCSIS ) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible (SIS) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, VCSIS provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barabasi-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric VCSIR is introduced to assess the robustness of networks with respect to the spread of susceptible/infected/recovered (SIR) epidemics. To compute VCSIR, we propose a novel individual-based approach to model the spread of SIR epidemics in networks, which captures the infection size for a given effective infection rate. Thus, VCSIR quantitatively integrates the infection strength with the corresponding infection size. To optimize the VCSIR metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation strategies. In summary, our work advances the network science field in assessing the robustness of complex networks with respect to various disturbing dynamics.

Social interaction in synthetic and natural microbial communities.

PubMed

Xavier, Joao B

2011-04-12

Social interaction among cells is essential for multicellular complexity. But how do molecular networks within individual cells confer the ability to interact? And how do those same networks evolve from the evolutionary conflict between individual- and population-level interests? Recent studies have dissected social interaction at the molecular level by analyzing both synthetic and natural microbial populations. These studies shed new light on the role of population structure for the evolution of cooperative interactions and revealed novel molecular mechanisms that stabilize cooperation among cells. New understanding of populations is changing our view of microbial processes, such as pathogenesis and antibiotic resistance, and suggests new ways to fight infection by exploiting social interaction. The study of social interaction is also challenging established paradigms in cancer evolution and immune system dynamics. Finding similar patterns in such diverse systems suggests that the same 'social interaction motifs' may be general to many cell populations.

Beyond the statistics of adolescent smoking.

PubMed Central

Eckert, P

1983-01-01

Statistical studies can identify the demographic characteristics of the adolescent smoking population but cannot reveal how clusters of demographic categories combine in the culture of the community to form salient social categories, or how social processes link these categories to smoking and smoking-related behavior. Because smoking and smoking-related behavior function as a key social symbol, anti-smoking campaigns that are based on an inaccurate understanding of the social context in which smoking occurs can reinforce this behavior. Participant observation in a suburban high school suggests that adolescents begin smoking as part of a complex symbolic process growing out of the process of social differentiation between future members of the working class on the one hand and the middle class on the other. It points out inadequacies in two existing anti-smoking programs in the schools that result from ignoring the social dynamics of smoking. PMID:6829827

The geometric preference subtype in ASD: identifying a consistent, early-emerging phenomenon through eye tracking.

PubMed

Moore, Adrienne; Wozniak, Madeline; Yousef, Andrew; Barnes, Cindy Carter; Cha, Debra; Courchesne, Eric; Pierce, Karen

2018-01-01

The wide range of ability and disability in ASD creates a need for tools that parse the phenotypic heterogeneity into meaningful subtypes. Using eye tracking, our past studies revealed that when presented with social and geometric images, a subset of ASD toddlers preferred viewing geometric images, and these toddlers also had greater symptom severity than ASD toddlers with greater social attention. This study tests whether this "GeoPref test" effect would generalize across different social stimuli. Two hundred and twenty-seven toddlers (76 ASD) watched a 90-s video, the Complex Social GeoPref test, of dynamic geometric images paired with social images of children interacting and moving. Proportion of visual fixation time and number of saccades per second to both images were calculated. To allow for cross-paradigm comparisons, a subset of 126 toddlers also participated in the original GeoPref test. Measures of cognitive and social functioning (MSEL, ADOS, VABS) were collected and related to eye tracking data. To examine utility as a diagnostic indicator to detect ASD toddlers, validation statistics (e.g., sensitivity, specificity, ROC, AUC) were calculated for the Complex Social GeoPref test alone and when combined with the original GeoPref test. ASD toddlers spent a significantly greater amount of time viewing geometric images than any other diagnostic group. Fixation patterns from ASD toddlers who participated in both tests revealed a significant correlation, supporting the idea that these tests identify a phenotypically meaningful ASD subgroup. Combined use of both original and Complex Social GeoPref tests identified a subgroup of about 1 in 3 ASD toddlers from the "GeoPref" subtype (sensitivity 35%, specificity 94%, AUC 0.75.) Replicating our previous studies, more time looking at geometric images was associated with significantly greater ADOS symptom severity. Regardless of the complexity of the social images used (low in the original GeoPref test vs high in the new Complex Social GeoPref test), eye tracking of toddlers can accurately identify a specific ASD "GeoPref" subtype with elevated symptom severity. The GeoPref tests are predictive of ASD at the individual subject level and thus potentially useful for various clinical applications (e.g., early identification, prognosis, or development of subtype-specific treatments).

Simulating drinking in social networks to inform alcohol prevention and treatment efforts.

PubMed

Hallgren, Kevin A; McCrady, Barbara S; Caudell, Thomas P; Witkiewitz, Katie; Tonigan, J Scott

2017-11-01

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A systematic literature review of the key challenges for developing the structure of public health economic models.

PubMed

Squires, Hazel; Chilcott, James; Akehurst, Ronald; Burr, Jennifer; Kelly, Michael P

2016-04-01

To identify the key methodological challenges for public health economic modelling and set an agenda for future research. An iterative literature search identified papers describing methodological challenges for developing the structure of public health economic models. Additional multidisciplinary literature searches helped expand upon important ideas raised within the review. Fifteen articles were identified within the formal literature search, highlighting three key challenges: inclusion of non-healthcare costs and outcomes; inclusion of equity; and modelling complex systems and multi-component interventions. Based upon these and multidisciplinary searches about dynamic complexity, the social determinants of health, and models of human behaviour, six areas for future research were specified. Future research should focus on: the use of systems approaches within health economic modelling; approaches to assist the systematic consideration of the social determinants of health; methods for incorporating models of behaviour and social interactions; consideration of equity; and methodology to help modellers develop valid, credible and transparent public health economic model structures.

Migration of cells in a social context

PubMed Central

Vedel, Søren; Tay, Savaş; Johnston, Darius M.; Bruus, Henrik; Quake, Stephen R.

2013-01-01

In multicellular organisms and complex ecosystems, cells migrate in a social context. Whereas this is essential for the basic processes of life, the influence of neighboring cells on the individual remains poorly understood. Previous work on isolated cells has observed a stereotypical migratory behavior characterized by short-time directional persistence with long-time random movement. We discovered a much richer dynamic in the social context, with significant variations in directionality, displacement, and speed, which are all modulated by local cell density. We developed a mathematical model based on the experimentally identified “cellular traffic rules” and basic physics that revealed that these emergent behaviors are caused by the interplay of single-cell properties and intercellular interactions, the latter being dominated by a pseudopod formation bias mediated by secreted chemicals and pseudopod collapse following collisions. The model demonstrates how aspects of complex biology can be explained by simple rules of physics and constitutes a rapid test bed for future studies of collective migration of individual cells. PMID:23251032

Migration of cells in a social context.

PubMed

Vedel, Søren; Tay, Savaş; Johnston, Darius M; Bruus, Henrik; Quake, Stephen R

2013-01-02

In multicellular organisms and complex ecosystems, cells migrate in a social context. Whereas this is essential for the basic processes of life, the influence of neighboring cells on the individual remains poorly understood. Previous work on isolated cells has observed a stereotypical migratory behavior characterized by short-time directional persistence with long-time random movement. We discovered a much richer dynamic in the social context, with significant variations in directionality, displacement, and speed, which are all modulated by local cell density. We developed a mathematical model based on the experimentally identified "cellular traffic rules" and basic physics that revealed that these emergent behaviors are caused by the interplay of single-cell properties and intercellular interactions, the latter being dominated by a pseudopod formation bias mediated by secreted chemicals and pseudopod collapse following collisions. The model demonstrates how aspects of complex biology can be explained by simple rules of physics and constitutes a rapid test bed for future studies of collective migration of individual cells.

Modeling human behavior in economics and social science.

PubMed

Dolfin, M; Leonida, L; Outada, N

2017-12-01

The complex interactions between human behaviors and social economic sciences is critically analyzed in this paper in view of possible applications of mathematical modeling as an attainable interdisciplinary approach to understand and simulate the aforementioned dynamics. The quest is developed along three steps: Firstly an overall analysis of social and economic sciences indicates the main requirements that a contribution of mathematical modeling should bring to these sciences; subsequently the focus moves to an overview of mathematical tools and to the selection of those which appear, according to the authors bias, appropriate to the modeling; finally, a survey of applications is presented looking ahead to research perspectives. Copyright © 2017 Elsevier B.V. All rights reserved.

Social sciences research in neglected tropical diseases 2: A bibliographic analysis

PubMed Central

2011-01-01

Background There are strong arguments for social science and interdisciplinary research in the neglected tropical diseases. These diseases represent a rich and dynamic interplay between vector, host, and pathogen which occurs within social, physical and biological contexts. The overwhelming sense, however, is that neglected tropical diseases research is a biomedical endeavour largely excluding the social sciences. The purpose of this review is to provide a baseline for discussing the quantum and nature of the science that is being conducted, and the extent to which the social sciences are a part of that. Methods A bibliographic analysis was conducted of neglected tropical diseases related research papers published over the past 10 years in biomedical and social sciences. The analysis had textual and bibliometric facets, and focussed on chikungunya, dengue, visceral leishmaniasis, and onchocerciasis. Results There is substantial variation in the number of publications associated with each disease. The proportion of the research that is social science based appears remarkably consistent (<4%). A textual analysis, however, reveals a degree of misclassification by the abstracting service where a surprising proportion of the "social sciences" research was pure clinical research. Much of the social sciences research also tends to be "hand maiden" research focused on the implementation of biomedical solutions. Conclusion There is little evidence that scientists pay any attention to the complex social, cultural, biological, and environmental dynamic involved in human pathogenesis. There is little investigator driven social science and a poor presence of interdisciplinary science. The research needs more sophisticated funders and priority setters who are not beguiled by uncritical biomedical promises. PMID:21210997

Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

PubMed Central

Hasson, Uri; Frith, Chris D.

2016-01-01

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader–follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis PMID:27069044

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

NASA Astrophysics Data System (ADS)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

Social and professional influences on antimicrobial prescribing for doctors-in-training: a realist review

PubMed Central

Papoutsi, Chrysanthi; Mattick, Karen; Pearson, Mark; Brennan, Nicola; Briscoe, Simon; Wong, Geoff

2017-01-01

Abstract Background Antimicrobial resistance has led to widespread implementation of interventions for appropriate prescribing. However, such interventions are often adopted without an adequate understanding of the challenges facing doctors-in-training as key prescribers. Methods The review followed a realist, theory-driven approach to synthesizing qualitative, quantitative and mixed-methods literature. Consistent with realist review quality standards, articles retrieved from electronic databases were systematically screened and analysed to elicit explanations of antimicrobial prescribing behaviours. These explanations were consolidated into a programme theory drawing on social science and learning theory, and shaped though input from patients and practitioners. Results By synthesizing data from 131 articles, the review highlights the complex social and professional dynamics underlying antimicrobial prescribing decisions of doctors-in-training. The analysis shows how doctors-in-training often operate within challenging contexts (hierarchical relationships, powerful prescribing norms, unclear roles and responsibilities, implicit expectations about knowledge levels, uncertainty about application of knowledge in practice) where they prioritize particular responses (fear of criticism and individual responsibility, managing one’s reputation and position in the team, appearing competent). These complex dynamics explain how and why doctors-in-training decide to: (i) follow senior clinicians’ prescribing habits; (ii) take (or not) into account prescribing aids, advice from other health professionals or patient expectations; and (iii) ask questions or challenge decisions. This increased understanding allows for targeted tailoring, design and implementation of antimicrobial prescribing interventions. Conclusions This review contributes to a better understanding of how antimicrobial prescribing interventions for doctors-in-training can be embedded more successfully in the hierarchical and inter-professional dynamics of different healthcare settings. PMID:28859445

Commons problems, common ground: Earth-surface dynamics and the social-physical interdisciplinary frontier

NASA Astrophysics Data System (ADS)

Lazarus, E.

2015-12-01

In the archetypal "tragedy of the commons" narrative, local farmers pasture their cows on the town common. Soon the common becomes crowded with cows, who graze it bare, and the arrangement of open access to a shared resource ultimately fails. The "tragedy" involves social and physical processes, but the denouement depends on who is telling the story. An economist might argue that the system collapses because each farmer always has a rational incentive to graze one more cow. An ecologist might remark that the rate of grass growth is an inherent control on the common's carrying capacity. And a geomorphologist might point out that processes of soil degradation almost always outstrip processes of soil production. Interdisciplinary research into human-environmental systems still tends to favor disciplinary vantages. In the context of Anthropocene grand challenges - including fundamental insight into dynamics of landscape resilience, and what the dominance of human activities means for processes of change and evolution on the Earth's surface - two disciplines in particular have more to talk about than they might think. Here, I use three examples - (1) beach nourishment, (2) upstream/downstream fluvial asymmetry, and (3) current and historical "land grabbing" - to illustrate a range of interconnections between physical Earth-surface science and common-pool resource economics. In many systems, decision-making and social complexity exert stronger controls on landscape expression than do physical geomorphological processes. Conversely, human-environmental research keeps encountering multi-scale, emergent problems of resource use made 'common-pool' by water, nutrient and sediment transport dynamics. Just as Earth-surface research can benefit from decades of work on common-pool resource systems, quantitative Earth-surface science can make essential contributions to efforts addressing complex problems in environmental sustainability.

Evolution of natural risk: research framework and perspectives

NASA Astrophysics Data System (ADS)

Hufschmidt, G.; Crozier, M.; Glade, T.

2005-05-01

This study presents a conceptual framework for addressing temporal variation in natural risk. Numerous former natural risk analyses and investigations have demonstrated that time and related changes have a crucial influence on risk. For natural hazards, time becomes a factor for a number of reasons. Using the example of landslides to illustrate this point, it is shown that: 1. landslide history is important in determining probability of occurrence, 2. the significance of catchment variables in explaining landslide susceptibility is dependent on the time scale chosen, 3. the observer's perception of the geosystem's state changes with different time spans, and 4. the system's sensitivity varies with time. Natural hazards are not isolated events but complex features that are connected with the social system. Similarly, elements at risk and their vulnerability are highly dynamic through time, an aspect that is not sufficiently acknowledged in research. Since natural risk is an amalgam of hazard and vulnerability, its temporal behaviour has to be considered as well. Identifying these changes and their underlying processes contributes to a better understanding of natural risk today and in the future. However, no dynamic models for natural risks are currently available. Dynamic behaviour of factors affecting risk is likely to create increasing connectivity and complexity. This demands a broad approach to natural risk, since the concept of risk encapsulates aspects of many disciplines and has suffered from single-discipline approaches in the past. In New Zealand, dramatic environmental and social change has occurred in a relatively short period of time, graphically demonstrating the temporal variability of the geosystem and the social system. To understand these changes and subsequent interactions between both systems, a holistic perspective is needed. This contribution reviews available frameworks, demonstrates the need for further concepts, and gives research perspectives on a New Zealand example.

Statistical Mechanics of Temporal and Interacting Networks

NASA Astrophysics Data System (ADS)

Zhao, Kun

In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide a new framework to quantify the information encoded in these networks and to answer a fundamental problem in network science: how complex are temporal and growing networks. Finally, we consider two examples of critical phenomena in interacting networks. In particular, on one side we investigate the percolation of interacting networks by introducing antagonistic interactions. On the other side, we investigate a model of political election based on the percolation of antagonistic networks. The aim of this research is to show how antagonistic interactions change the physics of critical phenomena on interacting networks. We believe that the work presented in these thesis offers the possibility to appreciate the large variability of problems that can be addressed in the new framework of temporal and interacting networks.

Linking River Basin Modifications and Rural Soil and Water Management Practices in Tropical Deltas to Sea Level Rise Vulnerability

NASA Astrophysics Data System (ADS)

Rogers, K. G.; Brondizio, E.; Roy, K.; Syvitski, J. P.

2015-12-01

The increased vulnerability of deltaic communities to coastal flooding as a result of upstream engineering has been acknowledged for decades. What has received less attention is the sensitivity of deltas to the interactions between river basin modifications and local scale cultivation and irrigation. Combined with reduced river and sediment discharge, soil and water management practices in coastal areas may exacerbate the risk of tidal flooding, erosion of arable land, and salinization of soils and groundwater associated with sea level rise. This represents a cruel irony to smallholder subsistence farmers whose priorities are food, water and economic security, rather than sustainability of the environment. Such issues challenge disciplinary approaches and require integrated social-biophysical models able to understand and diagnose these complex relationships. This study applies a new conceptual framework to define the relevant social and physical units operating on the common pool resources of climate, water and sediment in the Bengal Delta (Bangladesh). The new framework will inform development of a nested geospatial analysis and a coupled model to identify multi-scale social-biophysical feedbacks associated with smallholder soil and water management practices, coastal dynamics, basin modification, and climate vulnerability in tropical deltas. The framework was used to create household surveys for collecting data on climate perceptions, land and water management, and governance. Test surveys were administered to rural farmers in 14 villages during a reconnaissance visit to coastal Bangladesh. Initial results demonstrate complexity and heterogeneity at the local scale in both biophysical conditions and decision-making. More importantly, the results illuminate how national and geopolitical-level policies scale down to impact local-level environmental and social stability in communities already vulnerable to coastal flooding. Here, we will discuss components of the new conceptual framework, present results from the test surveys, and demonstrate how the framework can be dynamically adapted to reflect complex interactions at multiple scales.

The social neuroscience and the theory of integrative levels.

PubMed

Bello-Morales, Raquel; Delgado-García, José María

2015-01-01

The theory of integrative levels provides a general description of the evolution of matter through successive orders of complexity and integration. Along its development, material forms pass through different levels of organization, such as physical, chemical, biological or sociological. The appearance of novel structures and dynamics during this process of development of matter in complex systems has been called emergence. Social neuroscience (SN), an interdisciplinary field that aims to investigate the biological mechanisms that underlie social structures, processes, and behavior and the influences between social and biological levels of organization, has affirmed the necessity for including social context as an essential element to understand the human behavior. To do this, SN proposes a multilevel integrative approach by means of three principles: multiple determinism, nonadditive determinism and reciprocal determinism. These theoretical principles seem to share the basic tenets of the theory of integrative levels but, in this paper, we aim to reveal the differences among both doctrines. First, SN asserts that combination of neural and social variables can produce emergent phenomena that would not be predictable from a neuroscientific or social psychological analysis alone; SN also suggests that to achieve a complete understanding of social structures we should use an integrative analysis that encompasses levels of organization ranging from the genetic level to the social one; finally, SN establishes that there can be mutual influences between biological and social factors in determining behavior, accepting, therefore, a double influence, upward from biology to social level, and downward, from social level to biology. In contrast, following the theory of integrative levels, emergent phenomena are not produced by the combination of variables from two levels, but by the increment of complexity at one level. In addition, the social behavior and structures might be contemplated not as the result of mixing or summing social and biological influences, but as emergent phenomena that should be described with its own laws. Finally, following the integrative levels view, influences upward, from biology to social level, and downward, from social level to biology, might not be equivalent, since the bottom-up processes are emergent and the downward causation (DC) is not.

The social neuroscience and the theory of integrative levels

PubMed Central

Bello-Morales, Raquel; Delgado-García, José María

2015-01-01

The theory of integrative levels provides a general description of the evolution of matter through successive orders of complexity and integration. Along its development, material forms pass through different levels of organization, such as physical, chemical, biological or sociological. The appearance of novel structures and dynamics during this process of development of matter in complex systems has been called emergence. Social neuroscience (SN), an interdisciplinary field that aims to investigate the biological mechanisms that underlie social structures, processes, and behavior and the influences between social and biological levels of organization, has affirmed the necessity for including social context as an essential element to understand the human behavior. To do this, SN proposes a multilevel integrative approach by means of three principles: multiple determinism, nonadditive determinism and reciprocal determinism. These theoretical principles seem to share the basic tenets of the theory of integrative levels but, in this paper, we aim to reveal the differences among both doctrines. First, SN asserts that combination of neural and social variables can produce emergent phenomena that would not be predictable from a neuroscientific or social psychological analysis alone; SN also suggests that to achieve a complete understanding of social structures we should use an integrative analysis that encompasses levels of organization ranging from the genetic level to the social one; finally, SN establishes that there can be mutual influences between biological and social factors in determining behavior, accepting, therefore, a double influence, upward from biology to social level, and downward, from social level to biology. In contrast, following the theory of integrative levels, emergent phenomena are not produced by the combination of variables from two levels, but by the increment of complexity at one level. In addition, the social behavior and structures might be contemplated not as the result of mixing or summing social and biological influences, but as emergent phenomena that should be described with its own laws. Finally, following the integrative levels view, influences upward, from biology to social level, and downward, from social level to biology, might not be equivalent, since the bottom-up processes are emergent and the downward causation (DC) is not. PMID:26578909

From the guest editors.

PubMed

Chowell, Gerardo; Feng, Zhilan; Song, Baojun

2013-01-01

Carlos Castilo-Chavez is a Regents Professor, a Joaquin Bustoz Jr. Professor of Mathematical Biology, and a Distinguished Sustainability Scientist at Arizona State University. His research program is at the interface of the mathematical and natural and social sciences with emphasis on (i) the role of dynamic social landscapes on disease dispersal; (ii) the role of environmental and social structures on the dynamics of addiction and disease evolution, and (iii) Dynamics of complex systems at the interphase of ecology, epidemiology and the social sciences. Castillo-Chavez has co-authored over two hundred publications (see goggle scholar citations) that include journal articles and edited research volumes. Specifically, he co-authored a textbook in Mathematical Biology in 2001 (second edition in 2012); a volume (with Harvey Thomas Banks) on the use of mathematical models in homeland security published in SIAM's Frontiers in Applied Mathematics Series (2003); and co-edited volumes in the Series Contemporary Mathematics entitled '' Mathematical Studies on Human Disease Dynamics: Emerging Paradigms and Challenges'' (American Mathematical Society, 2006) and Mathematical and Statistical Estimation Approaches in Epidemiology (Springer-Verlag, 2009) highlighting his interests in the applications of mathematics in emerging and re-emerging diseases. Castillo-Chavez is a member of the Santa Fe Institute's external faculty, adjunct professor at Cornell University, and contributor, as a member of the Steering Committee of the '' Committee for the Review of the Evaluation Data on the Effectiveness of NSF-Supported and Commercially Generated Mathematics Curriculum Materials,'' to a 2004 NRC report. The CBMS workshop '' Mathematical Epidemiology with Applications'' lectures delivered by C. Castillo-Chavez and F. Brauer in 2011 have been published by SIAM in 2013.

Challenges in the analysis of complex systems: introduction and overview

NASA Astrophysics Data System (ADS)

Hastings, Harold M.; Davidsen, Jörn; Leung, Henry

2017-12-01

One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.

Social Determinants and Health Behaviors: Conceptual Frames and Empirical Advances

PubMed Central

Short, Susan E.; Mollborn, Stefanie

2015-01-01

Health behaviors shape health and well-being in individuals and populations. Drawing on recent research, we review applications of the widely applied “social determinants” approach to health behaviors. This approach shifts the lens from individual attribution and responsibility to societal organization and the myriad institutions, structures, inequalities, and ideologies undergirding health behaviors. Recent scholarship integrates a social determinants perspective with biosocial approaches to health behavior dynamics. Empirical advances model feedback among social, psychological and biological factors. Health behaviors are increasingly recognized as multidimensional and embedded in health lifestyles, varying over the life course and across place and reflecting dialectic between structure and agency that necessitates situating individuals in context. Advances in measuring and modeling health behaviors promise to enhance representations of this complexity. PMID:26213711

Dynamical Behaviors in Complex-Valued Love Model With or Without Time Delays

NASA Astrophysics Data System (ADS)

Deng, Wei; Liao, Xiaofeng; Dong, Tao

2017-12-01

In this paper, a novel version of nonlinear model, i.e. a complex-valued love model with two time delays between two individuals in a love affair, has been proposed. A notable feature in this model is that we separate the emotion of one individual into real and imaginary parts to represent the variation and complexity of psychophysiological emotion in romantic relationship instead of just real domain, and make our model much closer to reality. This is because love is a complicated cognitive and social phenomenon, full of complexity, diversity and unpredictability, which refers to the coexistence of different aspects of feelings, states and attitudes ranging from joy and trust to sadness and disgust. By analyzing associated characteristic equation of linearized equations for our model, it is found that the Hopf bifurcation occurs when the sum of time delays passes through a sequence of critical value. Stability of bifurcating cyclic love dynamics is also derived by applying the normal form theory and the center manifold theorem. In addition, it is also shown that, for some appropriate chosen parameters, chaotic behaviors can appear even without time delay.

"My Body Speaks to Them": Instructor Reflections on the Complexities of Power and Social Embodiments

ERIC Educational Resources Information Center

Kannen, Victoria

2012-01-01

The dynamics of instructor embodiments and their relation to notions of power are explored in this paper. Informed by feminist poststructural theory, the author argues that, in classrooms where the focus of study is on conceptions of identity such as gender and race, the body of the instructor becomes an explicit pedagogical example. Through…

The human genome initiative: a statement of need.

PubMed

Watson, J D

1991-10-15

We may never have a complete understanding of the complex dynamics of the human organism, but we can and should know all our genes and begin to understand their role in the diseases that diminish our lives. A 15-year program has been projected and the specific, quantifiable goals in mapping and sequencing are outlined. Ethical, legal, and social implications are also discussed.

Systemic Engagement: Universities as Partners in Systemic Approaches to Community Change

ERIC Educational Resources Information Center

McNall, Miles A.; Barnes-Najor, Jessica V.; Brown, Robert E.; Doberneck, Diane M.; Fitzgerald, Hiram E.

2015-01-01

The most pressing social problems facing humanity in the 21st century are what systems theorist Russell Ackoff referred to as "messes"--complex dynamic systems of problems that interact and reinforce each other over time. In this article, the authors argue that the lack of progress in managing messes is in part due to the predominance of…

An ecosystemic approach to evaluating ecological, socioeconomic and group dynamics affecting the prevalence of Aedes aegypti in two Colombian towns.

PubMed

Quintero, Juliana; Carrasquilla, Gabriel; Suárez, Roberto; González, Catalina; Olano, Victor A

2009-01-01

This article focuses on the epidemiological methods and results of a global Ecohealth study that explored the complexity of the relationship between ecological, biological, economical, social and political factors and vector presence. The study was carried out in two dengue endemic areas of Colombia. A transdisciplinary team gathered quantitative and qualitative data. A survey in randomly sampled households was applied and, simultaneously, direct observation of potential breeding sites was carried out. Logistic regressions and qualitative techniques were used. Qualitative and quantitative data were compared using triangulation. The presence of low water containers increases seven-fold the risk of finding immature forms of Aedes aegypti in the household (OR = 7.5; 95%CI: 1.7-32.2). An inverse association between socioeconomic stratum and presence of the vector was identified (Low stratum OR = 0.9; 95%CI: 0.6-1.4; High stratum OR =0.4; 95%CI: 0.07-1.7). Water management is a complex social dynamic associated with the presence of Ae. aegypti. Dengue control is a challenge for public health authorities and researchers as they should address promotion and prevention strategies that take into account cultural, behavioral, socioeconomic and health factors.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Saving Human Lives: What Complexity Science and Information Systems can Contribute

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Brockmann, Dirk; Chadefaux, Thomas; Donnay, Karsten; Blanke, Ulf; Woolley-Meza, Olivia; Moussaid, Mehdi; Johansson, Anders; Krause, Jens; Schutte, Sebastian; Perc, Matjaž

2015-02-01

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Saving Human Lives: What Complexity Science and Information Systems can Contribute.

PubMed

Helbing, Dirk; Brockmann, Dirk; Chadefaux, Thomas; Donnay, Karsten; Blanke, Ulf; Woolley-Meza, Olivia; Moussaid, Mehdi; Johansson, Anders; Krause, Jens; Schutte, Sebastian; Perc, Matjaž

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Extended generalized recurrence plot quantification of complex circular patterns

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2017-03-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing patterns, turbulent spatial plankton patterns, and fractals. Determinism is a central measure in this framework quantifying the level of regularity of spatial structures. We show by basic examples of fully regular patterns of different symmetries that this measure underestimates the orderliness of circular patterns resulting from rotational symmetries. We overcome this crucial problem by checking additional structural elements of the generalized recurrence plot which is demonstrated with the examples. Furthermore, we show the potential of the extended quantity of determinism applying it to more irregular circular patterns which are generated by the complex Ginzburg-Landau-equation and which can be often observed in real spatially extended dynamical systems. So, we are able to reconstruct the main separations of the system's parameter space analyzing single snapshots of the real part only, in contrast to the use of the original quantity. This ability of the proposed method promises also an improved description of other systems with complicated spatio-temporal dynamics typically occurring in fluid dynamics, climatology, biology, ecology, social sciences, etc.

The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

PubMed

Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

2009-09-21

Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.

Dynamics of Disagreement: Large-Scale Temporal Network Analysis Reveals Negative Interactions in Online Collaboration

NASA Astrophysics Data System (ADS)

Tsvetkova, Milena; García-Gavilanes, Ruth; Yasseri, Taha

2016-11-01

Disagreement and conflict are a fact of social life. However, negative interactions are rarely explicitly declared and recorded and this makes them hard for scientists to study. In an attempt to understand the structural and temporal features of negative interactions in the community, we use complex network methods to analyze patterns in the timing and configuration of reverts of article edits to Wikipedia. We investigate how often and how fast pairs of reverts occur compared to a null model in order to control for patterns that are natural to the content production or are due to the internal rules of Wikipedia. Our results suggest that Wikipedia editors systematically revert the same person, revert back their reverter, and come to defend a reverted editor. We further relate these interactions to the status of the involved editors. Even though the individual reverts might not necessarily be negative social interactions, our analysis points to the existence of certain patterns of negative social dynamics within the community of editors. Some of these patterns have not been previously explored and carry implications for the knowledge collection practice conducted on Wikipedia. Our method can be applied to other large-scale temporal collaboration networks to identify the existence of negative social interactions and other social processes.

Emergence, institutionalization and renewal: Rhythms of adaptive governance in complex social-ecological systems.

PubMed

Chaffin, Brian C; Gunderson, Lance H

2016-01-01

Adaptive governance provides the capacity for environmental managers and decision makers to confront variable degrees of uncertainty inherent to complex social-ecological systems. Current theoretical conceptualizations of adaptive governance represent a series of structures and processes best suited for either adapting or transforming existing environmental governance regimes towards forms flexible enough to confront rapid ecological change. As the number of empirical examples of adaptive governance described in the literature grows, the conceptual basis of adaptive governance remains largely under theorized. We argue that reconnecting adaptive governance with foundational concepts of ecological resilience-specifically Panarchy and the adaptive cycle of complex systems-highlights the importance of episodic disturbances and cross-scale interactions in triggering reorganizations in governance. By envisioning the processes of adaptive governance through the lens of Panarchy, scholars and practitioners alike will be better able to identify the emergence of adaptive governance, as well as take advantage of opportunities to institutionalize this type of governance in pursuit of sustainability outcomes. The synergistic analysis of adaptive governance and Panarchy can provide critical insight for analyzing the role of social dynamics during oscillating periods of stability and instability in social-ecological systems. A deeper understanding of the potential for cross-scale interactions to shape adaptive governance regimes may be useful as society faces the challenge of mitigating the impacts of global environmental change. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolution of cooperation under social pressure in multiplex networks

NASA Astrophysics Data System (ADS)

Pereda, María

2016-09-01

In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.

Robot Comedy Lab: experimenting with the social dynamics of live performance

PubMed Central

Katevas, Kleomenis; Healey, Patrick G. T.; Harris, Matthew Tobias

2015-01-01

The success of live comedy depends on a performer's ability to “work” an audience. Ethnographic studies suggest that this involves the co-ordinated use of subtle social signals such as body orientation, gesture, gaze by both performers and audience members. Robots provide a unique opportunity to test the effects of these signals experimentally. Using a life-size humanoid robot, programmed to perform a stand-up comedy routine, we manipulated the robot's patterns of gesture and gaze and examined their effects on the real-time responses of a live audience. The strength and type of responses were captured using SHORE™computer vision analytics. The results highlight the complex, reciprocal social dynamics of performer and audience behavior. People respond more positively when the robot looks at them, negatively when it looks away and performative gestures also contribute to different patterns of audience response. This demonstrates how the responses of individual audience members depend on the specific interaction they're having with the performer. This work provides insights into how to design more effective, more socially engaging forms of robot interaction that can be used in a variety of service contexts. PMID:26379585

Neurobeachin and the Kinesin KIF21B Are Critical for Endocytic Recycling of NMDA Receptors and Regulate Social Behavior.

PubMed

Gromova, Kira V; Muhia, Mary; Rothammer, Nicola; Gee, Christine E; Thies, Edda; Schaefer, Irina; Kress, Sabrina; Kilimann, Manfred W; Shevchuk, Olga; Oertner, Thomas G; Kneussel, Matthias

2018-05-29

Autism spectrum disorders (ASDs) are associated with mutations affecting synaptic components, including GluN2B-NMDA receptors (NMDARs) and neurobeachin (NBEA). NBEA participates in biosynthetic pathways to regulate synapse receptor targeting, synaptic function, cognition, and social behavior. However, the role of NBEA-mediated transport in specific trafficking routes is unclear. Here, we highlight an additional function for NBEA in the local delivery and surface re-insertion of synaptic receptors in mouse neurons. NBEA dynamically interacts with Rab4-positive recycling endosomes, transiently enters spines in an activity-dependent manner, and regulates GluN2B-NMDAR recycling. Furthermore, we show that the microtubule growth inhibitor kinesin KIF21B constrains NBEA dynamics and is present in the NBEA-recycling endosome-NMDAR complex. Notably, Kif21b knockout decreases NMDAR surface expression and alters social behavior in mice, consistent with reported social deficits in Nbea mutants. The influence of NBEA-KIF21B interactions on GluN2B-NMDAR local recycling may be relevant to mechanisms underlying ASD etiology. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Interactions of social, terrestrial, and marine sub-systems in the Galapagos Islands, Ecuador.

PubMed

Walsh, Stephen J; Mena, Carlos F

2016-12-20

Galapagos is often cited as an example of the conflicts that are emerging between resource conservation and economic development in island ecosystems, as the pressures associated with tourism threaten nature, including the iconic and emblematic species, unique terrestrial landscapes, and special marine environments. In this paper, two projects are described that rely upon dynamic systems models and agent-based models to examine human-environment interactions. We use a theoretical context rooted in complexity theory to guide the development of our models that are linked to social-ecological dynamics. The goal of this paper is to describe key elements, relationships, and processes to inform and enhance our understanding of human-environment interactions in the Galapagos Islands of Ecuador. By formalizing our knowledge of how systems operate and the manner in which key elements are linked in coupled human-natural systems, we specify rules, relationships, and rates of exchange between social and ecological features derived through statistical functions and/or functions specified in theory or practice. The processes described in our models also have practical applications in that they emphasize how political policies generate different human responses and model outcomes, many detrimental to the social-ecological sustainability of the Galapagos Islands.

Evolution of cooperation under social pressure in multiplex networks.

PubMed

Pereda, María

2016-09-01

In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.

Recovery at Work: The Relationship Between Social Identity and Commitment Among Substance Abuse Counselors

PubMed Central

Curtis, Sara L.; Eby, Lillian T.

2010-01-01

The complex makeup of the substance abuse treatment workforce poses unique challenges to the field. One interesting dynamic is the high rate of counselors who are personally recovering from addictions. Based on social identity theory, it was expected that counselors working in the field of substance abuse treatment who are in recovery themselves will identify more with their profession and report higher professional and organizational commitment. Data from a study of substance abuse counselors from across the United States supports the proposed relationship between personal recovery status and professional commitment but not organizational commitment. PMID:20674241

Asia on the move: research challenges for population geography.

PubMed

Hugo, G

1996-06-01

This paper "summarises some of the major changes which have occurred in international migration to, from, and within Asia in the last two decades....A number of theoretical challenges are put forward regarding the complex interrelationships between international population movements, economic development and social change. The employment of systems approaches, neoclassical economic theory, social networks and institutional approaches, and the potential role of population geography in developing a more comprehensive explanation of the changing dynamics of international migration in the region, are discussed. Also considered are the gender dimension in migration, remittance flows and their consequences, and policy issues." excerpt

Society and the Carbon Cycle: A Social Science Perspective

NASA Astrophysics Data System (ADS)

Romero-Lankao, P.

2017-12-01

Societal activities, actions, and practices affect the carbon cycle and the climate of North America in complex ways. Carbon is a key component for the functioning of croplands, grasslands, forests. Carbon fuels our industry, transportation (vehicles and roadways), buildings, and other structures. Drawing on results from the SOCCR-2, this presentation uses a social science perspective to address three scientific questions. How do human actions and activities affect the carbon cycle? How human systems such as cities, agricultural field and forests are affected by changes in the carbon cycle? How is carbon management enabled and constraint by socio-political dynamics?

How is shrimp aquaculture transforming coastal livelihoods and lagoons in Estero Real, Nicaragua? The need to integrate social-ecological research and ecosystem-based approaches.

PubMed

Benessaiah, Karina; Sengupta, Raja

2014-08-01

Ecosystem-based approaches to aquaculture integrate environmental concerns into planning. Social-ecological systems research can improve this approach by explicitly relating ecological and social dynamics of change at multiple scales. Doing so requires not only addressing direct effects of aquaculture but also considering indirect factors such as changes in livelihood strategies, governance dynamics, and power relations. We selected the community of Puerto Morazán, Nicaragua as a case study to demonstrate how the introduction of small-scale aquaculture radically transformed another key livelihood activity, lagoon shrimp fishing, and the effects that these changes have had on lagoons and the people that depend on them. We find that shrimp aquaculture played a key role in the collapse, in the 1990s, of an existing lagoon common-property management. Shrimp aquaculture-related capital enabled the adoption of a new fishing technique that not only degraded lagoons but also led to their gradual privatization. The existence of social ties between small-scale shrimp farmers and other community members mitigated the impacts of privatization, illustrating the importance of social capital. Since 2008, community members are seeking to communally manage the lagoons once again, in response to degraded environmental conditions and a consolidation of the shrimp industry at the expense of smaller actors. This research shows that shrimp aquaculture intersects with a complex set of drivers, affecting not only how ecosystems are managed but also how they are perceived and valued. Understanding these social-ecological dynamics is essential to implement realistic policies and management of mangrove ecosystems and address the needs of resource-dependent people.

A cooperative game framework for detecting overlapping communities in social networks

NASA Astrophysics Data System (ADS)

Jonnalagadda, Annapurna; Kuppusamy, Lakshmanan

2018-02-01

Community detection in social networks is a challenging and complex task, which received much attention from researchers of multiple domains in recent years. The evolution of communities in social networks happens merely due to the self-interest of the nodes. The interesting feature of community structure in social networks is the multi membership of the nodes resulting in overlapping communities. Assuming the nodes of the social network as self-interested players, the dynamics of community formation can be captured in the form of a game. In this paper, we propose a greedy algorithm, namely, Weighted Graph Community Game (WGCG), in order to model the interactions among the self-interested nodes of the social network. The proposed algorithm employs the Shapley value mechanism to discover the inherent communities of the underlying social network. The experimental evaluation on the real-world and synthetic benchmark networks demonstrates that the performance of the proposed algorithm is superior to the state-of-the-art overlapping community detection algorithms.

The eukaryotic genome is structurally and functionally more like a social insect colony than a book.

PubMed

Qiu, Guo-Hua; Yang, Xiaoyan; Zheng, Xintian; Huang, Cuiqin

2017-11-01

Traditionally, the genome has been described as the 'book of life'. However, the metaphor of a book may not reflect the dynamic nature of the structure and function of the genome. In the eukaryotic genome, the number of centrally located protein-coding sequences is relatively constant across species, but the amount of noncoding DNA increases considerably with the increase of organismal evolutional complexity. Therefore, it has been hypothesized that the abundant peripheral noncoding DNA protects the genome and the central protein-coding sequences in the eukaryotic genome. Upon comparison with the habitation, sociality and defense mechanisms of a social insect colony, it is found that the genome is similar to a social insect colony in various aspects. A social insect colony may thus be a better metaphor than a book to describe the spatial organization and physical functions of the genome. The potential implications of the metaphor are also discussed.

Locating privileged spreaders on an online social network.

PubMed

Borge-Holthoefer, Javier; Rivero, Alejandro; Moreno, Yamir

2012-06-01

Social media have provided plentiful evidence of their capacity for information diffusion. Fads and rumors but also social unrest and riots travel fast and affect large fractions of the population participating in online social networks (OSNs). This has spurred much research regarding the mechanisms that underlie social contagion, and also who (if any) can unleash system-wide information dissemination. Access to real data, both regarding topology--the network of friendships--and dynamics--the actual way in which OSNs users interact, is crucial to decipher how the former facilitates the latter's success, understood as efficiency in information spreading. With the quantitative analysis that stems from complex network theory, we discuss who (and why) has privileged spreading capabilities when it comes to information diffusion. This is done considering the evolution of an episode of political protest which took place in Spain, spanning one month in 2011.

StreamExplorer: A Multi-Stage System for Visually Exploring Events in Social Streams.

PubMed

Wu, Yingcai; Chen, Zhutian; Sun, Guodao; Xie, Xiao; Cao, Nan; Liu, Shixia; Cui, Weiwei

2017-10-18

Analyzing social streams is important for many applications, such as crisis management. However, the considerable diversity, increasing volume, and high dynamics of social streams of large events continue to be significant challenges that must be overcome to ensure effective exploration. We propose a novel framework by which to handle complex social streams on a budget PC. This framework features two components: 1) an online method to detect important time periods (i.e., subevents), and 2) a tailored GPU-assisted Self-Organizing Map (SOM) method, which clusters the tweets of subevents stably and efficiently. Based on the framework, we present StreamExplorer to facilitate the visual analysis, tracking, and comparison of a social stream at three levels. At a macroscopic level, StreamExplorer uses a new glyph-based timeline visualization, which presents a quick multi-faceted overview of the ebb and flow of a social stream. At a mesoscopic level, a map visualization is employed to visually summarize the social stream from either a topical or geographical aspect. At a microscopic level, users can employ interactive lenses to visually examine and explore the social stream from different perspectives. Two case studies and a task-based evaluation are used to demonstrate the effectiveness and usefulness of StreamExplorer.Analyzing social streams is important for many applications, such as crisis management. However, the considerable diversity, increasing volume, and high dynamics of social streams of large events continue to be significant challenges that must be overcome to ensure effective exploration. We propose a novel framework by which to handle complex social streams on a budget PC. This framework features two components: 1) an online method to detect important time periods (i.e., subevents), and 2) a tailored GPU-assisted Self-Organizing Map (SOM) method, which clusters the tweets of subevents stably and efficiently. Based on the framework, we present StreamExplorer to facilitate the visual analysis, tracking, and comparison of a social stream at three levels. At a macroscopic level, StreamExplorer uses a new glyph-based timeline visualization, which presents a quick multi-faceted overview of the ebb and flow of a social stream. At a mesoscopic level, a map visualization is employed to visually summarize the social stream from either a topical or geographical aspect. At a microscopic level, users can employ interactive lenses to visually examine and explore the social stream from different perspectives. Two case studies and a task-based evaluation are used to demonstrate the effectiveness and usefulness of StreamExplorer.

Fluctuation of similarity to detect transitions between distinct dynamical regimes in short time series

NASA Astrophysics Data System (ADS)

Malik, Nishant; Marwan, Norbert; Zou, Yong; Mucha, Peter J.; Kurths, Jürgen

2014-06-01

A method to identify distinct dynamical regimes and transitions between those regimes in a short univariate time series was recently introduced [N. Malik et al., Europhys. Lett. 97, 40009 (2012), 10.1209/0295-5075/97/40009], employing the computation of fluctuations in a measure of nonlinear similarity based on local recurrence properties. In this work, we describe the details of the analytical relationships between this newly introduced measure and the well-known concepts of attractor dimensions and Lyapunov exponents. We show that the new measure has linear dependence on the effective dimension of the attractor and it measures the variations in the sum of the Lyapunov spectrum. To illustrate the practical usefulness of the method, we identify various types of dynamical transitions in different nonlinear models. We present testbed examples for the new method's robustness against noise and missing values in the time series. We also use this method to analyze time series of social dynamics, specifically an analysis of the US crime record time series from 1975 to 1993. Using this method, we find that dynamical complexity in robberies was influenced by the unemployment rate until the late 1980s. We have also observed a dynamical transition in homicide and robbery rates in the late 1980s and early 1990s, leading to increase in the dynamical complexity of these rates.

Role-separating ordering in social dilemmas controlled by topological frustration

NASA Astrophysics Data System (ADS)

Amaral, Marco A.; Perc, Matjaž; Wardil, Lucas; Szolnoki, Attila; da Silva Júnior, Elton J.; da Silva, Jafferson K. L.

2017-03-01

``Three is a crowd" is an old proverb that applies as much to social interactions as it does to frustrated configurations in statistical physics models. Accordingly, social relations within a triangle deserve special attention. With this motivation, we explore the impact of topological frustration on the evolutionary dynamics of the snowdrift game on a triangular lattice. This topology provides an irreconcilable frustration, which prevents anticoordination of competing strategies that would be needed for an optimal outcome of the game. By using different strategy updating protocols, we observe complex spatial patterns in dependence on payoff values that are reminiscent to a honeycomb-like organization, which helps to minimize the negative consequence of the topological frustration. We relate the emergence of these patterns to the microscopic dynamics of the evolutionary process, both by means of mean-field approximations and Monte Carlo simulations. For comparison, we also consider the same evolutionary dynamics on the square lattice, where of course the topological frustration is absent. However, with the deletion of diagonal links of the triangular lattice, we can gradually bridge the gap to the square lattice. Interestingly, in this case the level of cooperation in the system is a direct indicator of the level of topological frustration, thus providing a method to determine frustration levels in an arbitrary interaction network.

Role-separating ordering in social dilemmas controlled by topological frustration.

PubMed

Amaral, Marco A; Perc, Matjaž; Wardil, Lucas; Szolnoki, Attila; da Silva Júnior, Elton J; da Silva, Jafferson K L

2017-03-01

''Three is a crowd" is an old proverb that applies as much to social interactions as it does to frustrated configurations in statistical physics models. Accordingly, social relations within a triangle deserve special attention. With this motivation, we explore the impact of topological frustration on the evolutionary dynamics of the snowdrift game on a triangular lattice. This topology provides an irreconcilable frustration, which prevents anticoordination of competing strategies that would be needed for an optimal outcome of the game. By using different strategy updating protocols, we observe complex spatial patterns in dependence on payoff values that are reminiscent to a honeycomb-like organization, which helps to minimize the negative consequence of the topological frustration. We relate the emergence of these patterns to the microscopic dynamics of the evolutionary process, both by means of mean-field approximations and Monte Carlo simulations. For comparison, we also consider the same evolutionary dynamics on the square lattice, where of course the topological frustration is absent. However, with the deletion of diagonal links of the triangular lattice, we can gradually bridge the gap to the square lattice. Interestingly, in this case the level of cooperation in the system is a direct indicator of the level of topological frustration, thus providing a method to determine frustration levels in an arbitrary interaction network.

Local Variation of Hashtag Spike Trains and Popularity in Twitter

PubMed Central

Sanlı, Ceyda; Lambiotte, Renaud

2015-01-01

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamical properties, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media. PMID:26161650

Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

On the basis of dynamical principles we i) advance a derivation of the Logistic Equation (LE), widely employed (among multiple applications) in the simulation of population growth, and ii) demonstrate that scale-invariance and a mean-value constraint are sufficient and necessary conditions for obtaining it. We also generalize the LE to multi-component systems and show that the above dynamical mechanisms underlie a large number of scale-free processes. Examples are presented regarding city-populations, diffusion in complex networks, and popularity of technological products, all of them obeying the multi-component logistic equation in an either stochastic or deterministic way.

System Dynamics Modeling of Transboundary Systems: The Bear River Basin Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Sehlke; Jake Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and groundwater data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or groundwater modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

System Dynamics Modeling of Transboundary Systems: the Bear River Basin Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerald Sehlke; Jacob J. Jacobson

2005-09-01

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multi-purpose national laboratory managed by the Department of Energy, has developed a systems dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River Basin, a transboundary basin that includes portions of Idaho,more » Utah and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple “what-if” scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause–effect relationships in large-scale hydrological systems; for integrating disparate data; for incorporating output from traditional hydraulic/hydrologic models; and for integration of interdisciplinary data, information and criteria to support better management decisions.« less

Four not six: Revealing culturally common facial expressions of emotion.

PubMed

Jack, Rachael E; Sun, Wei; Delis, Ioannis; Garrod, Oliver G B; Schyns, Philippe G

2016-06-01

As a highly social species, humans generate complex facial expressions to communicate a diverse range of emotions. Since Darwin's work, identifying among these complex patterns which are common across cultures and which are culture-specific has remained a central question in psychology, anthropology, philosophy, and more recently machine vision and social robotics. Classic approaches to addressing this question typically tested the cross-cultural recognition of theoretically motivated facial expressions representing 6 emotions, and reported universality. Yet, variable recognition accuracy across cultures suggests a narrower cross-cultural communication supported by sets of simpler expressive patterns embedded in more complex facial expressions. We explore this hypothesis by modeling the facial expressions of over 60 emotions across 2 cultures, and segregating out the latent expressive patterns. Using a multidisciplinary approach, we first map the conceptual organization of a broad spectrum of emotion words by building semantic networks in 2 cultures. For each emotion word in each culture, we then model and validate its corresponding dynamic facial expression, producing over 60 culturally valid facial expression models. We then apply to the pooled models a multivariate data reduction technique, revealing 4 latent and culturally common facial expression patterns that each communicates specific combinations of valence, arousal, and dominance. We then reveal the face movements that accentuate each latent expressive pattern to create complex facial expressions. Our data questions the widely held view that 6 facial expression patterns are universal, instead suggesting 4 latent expressive patterns with direct implications for emotion communication, social psychology, cognitive neuroscience, and social robotics. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Exploring the dynamics of research collaborations by mapping social networks in invasion science.

PubMed

Abrahams, B; Sitas, N; Esler, K J

2018-06-19

Moving towards more integrative approaches within the invasion sciences has been recognized as a means of improving linkages between science, policy, and practice. Yet despite the recognition that biological invasions pose complex social-ecological challenges, the invasion literature poorly covers social-ecological or distinctly integrative research. Various initiatives and investments have been made towards building research capacity and conducting more integrative research aimed at improving the management of biological invasions. Using a combination of social network and thematic analysis approaches, and the South African Working for Water (WfW) program as a case study for the management of invasive species, we identify and explore the roles of core authors in shaping collaboration networks and research outputs, based on bibliographic records. We found that research produced under the auspices of WfW is authored by a handful of core authors, conducting primarily ecologically-focused research, with social research significantly underrepresented. Core authors identified in this study play an essential role in mediating relationships between researchers, in addition to potentially controlling access to those seeking to form collaborations, maintaining network cohesion and connectivity across institutional and disciplinary boundaries. Research projects should be designed to span disciplines and institutions if they are to adequately address complex challenges. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

PubMed Central

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

Multiple visions of Indonesia's mud volcano: understanding representations of disaster across discursive settings.

PubMed

Drake, Phillip

2016-04-01

The Lapindo mudflow is one of the most controversial disasters in Indonesian history. Despite its unique biophysical features, most consider the mudflow a social disaster as scientific conflicts about its main trigger have evolved into legal disputes over accountability and rights. This paper examines this 'trigger debate', the stakes of scientific contention and the broader social and natural dynamics that shape the terms of this debate. A Latourian impulse drives this analysis, which aims to improve both understandings of--and responses to--complex disasters. This paper also notes that the stakes of representation extend to constructions of its stakeholders, especially to victims. As socionatural disasters become an increasingly common feature of the contemporary world, from mud volcanoes to extreme weather events caused by global warming, it is more important than ever to understand the dynamics of representing disasters and stakeholders. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.

The Dynamics of Protest Recruitment through an Online Network

NASA Astrophysics Data System (ADS)

González-Bailón, Sandra; Borge-Holthoefer, Javier; Rivero, Alejandro; Moreno, Yamir

2011-12-01

The recent wave of mobilizations in the Arab world and across Western countries has generated much discussion on how digital media is connected to the diffusion of protests. We examine that connection using data from the surge of mobilizations that took place in Spain in May 2011. We study recruitment patterns in the Twitter network and find evidence of social influence and complex contagion. We identify the network position of early participants (i.e. the leaders of the recruitment process) and of the users who acted as seeds of message cascades (i.e. the spreaders of information). We find that early participants cannot be characterized by a typical topological position but spreaders tend to be more central in the network. These findings shed light on the connection between online networks, social contagion, and collective dynamics, and offer an empirical test to the recruitment mechanisms theorized in formal models of collective action.

The dynamics of protest recruitment through an online network.

PubMed

González-Bailón, Sandra; Borge-Holthoefer, Javier; Rivero, Alejandro; Moreno, Yamir

2011-01-01

The recent wave of mobilizations in the Arab world and across Western countries has generated much discussion on how digital media is connected to the diffusion of protests. We examine that connection using data from the surge of mobilizations that took place in Spain in May 2011. We study recruitment patterns in the Twitter network and find evidence of social influence and complex contagion. We identify the network position of early participants (i.e. the leaders of the recruitment process) and of the users who acted as seeds of message cascades (i.e. the spreaders of information). We find that early participants cannot be characterized by a typical topological position but spreaders tend to be more central in the network. These findings shed light on the connection between online networks, social contagion, and collective dynamics, and offer an empirical test to the recruitment mechanisms theorized in formal models of collective action.

The disorganized family: institutions, practices and normativity.

PubMed

Smyth, Lisa

2016-12-01

This paper considers the value of a normative account of the relationship between agents and institutions for contemporary efforts to explain ever more complex and disorganized forms of social life. The character of social institutions, as they relate to practices, agents and norms, is explored through an engagement with the common claim that family life has been de-institutionalized. The paper argues that a normative rather than empirical definition of institutions avoids a false distinction between institutions and practices. Drawing on ideas of social freedom and creative action from critical theory, the changes in family life are explained not as an effect of de-institutionalization, but as a shift from an organized to a disorganized institutional type. This is understood as a response to changes in the wider normative structure, as a norm of individual freedom has undermined the legitimacy of the organized patriarchal nuclear family, with gender ascribed roles and associated duties. Contemporary motherhood is drawn on to illustrate the value of analysing the dynamic interactions between institutions, roles and practices for capturing both the complexity and the patterned quality of social experience. © London School of Economics and Political Science 2016.

Modeling the effects of social impact on epidemic spreading in complex networks

NASA Astrophysics Data System (ADS)

Ni, Shunjiang; Weng, Wenguo; Zhang, Hui

2011-11-01

We investigate by mean-field analysis and extensive simulations the effects of social impact on epidemic spreading in various typical networks with two types of nodes: active nodes and passive nodes, of which the behavior patterns are modeled according to the social impact theory. In this study, nodes are not only the media to spread the virus, but also disseminate their opinions on the virus-whether there is a need for certain self-protection measures to be taken to reduce the risk of being infected. Our results indicate that the interaction between epidemic spreading and opinion dynamics can have significant influences on the spreading of infectious diseases and related applications, such as the implementation of prevention and control measures against the infectious diseases.

Parsing heterogeneity in autism spectrum disorders: visual scanning of dynamic social scenes in school-aged children.

PubMed

Rice, Katherine; Moriuchi, Jennifer M; Jones, Warren; Klin, Ami

2012-03-01

To examine patterns of variability in social visual engagement and their relationship to standardized measures of social disability in a heterogeneous sample of school-aged children with autism spectrum disorders (ASD). Eye-tracking measures of visual fixation during free-viewing of dynamic social scenes were obtained for 109 children with ASD (mean age, 10.2 ± 3.2 years), 37 of whom were matched with 26 typically-developing (TD) children (mean age, 9.5 ± 2.2 years) on gender, age, and IQ. The smaller subset allowed between-group comparisons, whereas the larger group was used for within-group examinations of ASD heterogeneity. Between-group comparisons revealed significantly attenuated orientation to socially salient aspects of the scenes, with the largest effect size (Cohen's d = 1.5) obtained for reduced fixation on faces. Within-group analyses revealed a robust association between higher fixation on the inanimate environment and greater social disability. However, the associations between fixation on the eyes and mouth and social adaptation varied greatly, even reversing, when comparing different cognitive profile subgroups. Although patterns of social visual engagement with naturalistic social stimuli are profoundly altered in children with ASD, the social adaptivity of these behaviors varies for different groups of children. This variation likely represents different patterns of adaptation and maladaptation that should be traced longitudinally to the first years of life, before complex interactions between early predispositions and compensatory learning take place. We propose that variability in these early mechanisms of socialization may serve as proximal behavioral manifestations of genetic vulnerabilities. Copyright © 2012 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

The Butcher, the Baker, and the Candlestick Maker: John Dewey's Philosophy of Art Experience Saving Twenty-First-Century Art Education from Limbo

ERIC Educational Resources Information Center

Jones, Anne G.; Risku, Michael T.

2015-01-01

To satisfy the demands of society, the scholar-­practitioner in today's complex world of education must juggle various factors that are related to one another: practice, poiesis, or the creative act, culture, knowledge, and learning. These demands include adherence to education, law, politics, economics, ethics, equity, and social dynamics. The…

The Impact of Heterogeneity on Threshold-Limited Social Contagion, and on Crowd Decision-Making

NASA Astrophysics Data System (ADS)

Karampourniotis, Panagiotis Dimitrios

Recent global events and their poor predictability are often attributed to the complexity of the world event dynamics. A key factor generating the turbulence is human diversity. Here, we study the impact of heterogeneity of individuals on opinion formation and emergence of global biases. In the case of opinion formation, we focus on the heterogeneity of individuals' susceptibility to new ideas. In the case of global biases, we focus on the aggregated heterogeneity of individuals in a country. First, to capture the complex nature of social influencing we use a simple but classic model of contagion spreading in complex social systems, namely the threshold model. We investigate numerically and analytically the transition in the behavior of threshold-limited cascades in the presence of multiple initiators as the distribution of thresholds is varied between the two extreme cases of identical thresholds and a uniform distribution. We show that individuals' heterogeneity of susceptibility governs the dynamics, resulting in different sizes of initiators needed for consensus. Furthermore, given the impact of heterogeneity on the cascade dynamics, we investigate selection strategies for accelerating consensus. To this end, we introduce two new selection strategies for Influence Maximization. One of them focuses on finding the balance between targeting nodes which have high resistance to adoptions versus nodes positioned in central spots in networks. The second strategy focuses on the combination of nodes for reaching consensus, by targeting nodes which increase the group's influence. Our strategies outperform other existing strategies regardless of the susceptibility diversity and network degree assortativity. Finally, we study the aggregated biases of humans in a global setting. The emergence of technology and globalization gives raise to the debate on whether the world moves towards becoming flat, a world where preferential attachment does not govern economic growth. By studying the data from a global lending platform we discover that geographical proximity and cultural affinity are highly negatively correlated with levels of flatness of the world. Furthermore, we investigate the robustness of the flatness of the world against sudden catastrophic national events such as political disruptions, by removing countries (nodes) or connections (edges) between them.

Innovation, imitation, and problem-solving in a networked group.

PubMed

Wisdom, Thomas N; Goldstone, Robert L

2011-04-01

We implemented a problem-solving task in which groups of participants simultaneously played a simple innovation game in a complex problem space, with score feedback provided after each of a number of rounds. Each participant in a group was allowed to view and imitate the guesses of others during the game. The results showed the use of social learning strategies previously studied in other species, and demonstrated benefits of social learning and nonlinear effects of group size on strategy and performance. Rather than simply encouraging conformity, groups provided information to each individual about the distribution of useful innovations in the problem space. Imitation facilitated innovation rather than displacing it, because the former allowed good solutions to be propagated and preserved for further cumulative innovations in the group. Participants generally improved their solutions through the use of fairly conservative strategies, such as changing only a small portion of one's solution at a time, and tending to imitate solutions similar to one's own. Changes in these strategies over time had the effect of making solutions increasingly entrenched, both at individual and group levels. These results showed evidence of nonlinear dynamics in the decentralization of innovation, the emergence of group phenomena from complex interactions of individual efforts, stigmergy in the use of social information, and dynamic tradeoffs between exploration and exploitation of solutions. These results also support the idea that innovation and creativity can be recognized at the group level even when group members are generally cautious and imitative.

Magnetic storms and solar flares: can be analysed within similar mathematical framework with other extreme events?

NASA Astrophysics Data System (ADS)

Balasis, Georgios; Potirakis, Stelios M.; Papadimitriou, Constantinos; Zitis, Pavlos I.; Eftaxias, Konstantinos

2015-04-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to different extreme events, in order to support the suggestion that a dynamical analogy characterizes the generation of a single magnetic storm, solar flare, earthquake (in terms of pre-seismic electromagnetic signals) , epileptic seizure, and economic crisis. The analysis reveals that all the above mentioned different extreme events can be analyzed within similar mathematical framework. More precisely, we show that the populations of magnitudes of fluctuations included in all the above mentioned pulse-like-type time series follow the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar nonextensive q-parameter values. Moreover, based on a multidisciplinary statistical analysis we show that the extreme events are characterized by crucial common symptoms, namely: (i) high organization, high compressibility, low complexity, high information content; (ii) strong persistency; and (iii) existence of clear preferred direction of emerged activities. These symptoms clearly discriminate the appearance of the extreme events under study from the corresponding background noise.

Socio-affective touch expression database

PubMed Central

Op de Beeck, Hans

2018-01-01

Socio-affective touch communication conveys a vast amount of information about emotions and intentions in social contexts. In spite of the complexity of the socio-affective touch expressions we use daily, previous studies addressed only a few aspects of social touch mainly focusing on hedonics, such as stroking, leaving a wide range of social touch behaviour unexplored. To overcome this limit, we present the Socio-Affective Touch Expression Database (SATED), which includes a large range of dynamic interpersonal socio-affective touch events varying in valence and arousal. The original database contained 26 different social touch expressions each performed by three actor pairs. To validate each touch expression, we conducted two behavioural experiments investigating perceived naturalness and affective values. Based on the rated naturalness and valence, 13 socio-affective touch expressions along with 12 corresponding non-social touch events were selected as a complete set, achieving 75 video clips in total. Moreover, we quantified motion energy for each touch expression to investigate its intrinsic correlations with perceived affective values and its similarity among actor- and action-pairs. As a result, the touch expression database is not only systematically defined and well-controlled, but also spontaneous and natural, while eliciting clear affective responses. This database will allow a fine-grained investigation of complex interpersonal socio-affective touch in the realm of social psychology and neuroscience along with potential application areas in affective computing and neighbouring fields. PMID:29364988

Exploring the application of an evolutionary educational complex systems framework to teaching and learning about issues in the science and technology classroom

NASA Astrophysics Data System (ADS)

Yoon, Susan Anne

Understanding the world through a complex systems lens has recently garnered a great deal of interest in many knowledge disciplines. In the educational arena, interactional studies, through their focus on understanding patterns of system behaviour including the dynamical processes and trajectories of learning, lend support for investigating how a complex systems approach can inform educational research. This study uses previously existing literature and tools for complex systems applications and seeks to extend this research base by exploring learning outcomes of a complex systems framework when applied to curriculum and instruction. It is argued that by applying the evolutionary dynamics of variation, interaction and selection, complexity may be harnessed to achieve growth in both the social and cognitive systems of the classroom. Furthermore, if the goal of education, i.e., the social system under investigation, is to teach for understanding, conceptual knowledge of the kind described in Popper's (1972; 1976) World 3, needs to evolve. Both the study of memetic processes and knowledge building pioneered by Bereiter (cf. Bereiter, 2002) draw on the World 3 notion of ideas existing as conceptual artifacts that can be investigated as products outside of the individual mind providing an educational lens from which to proceed. The curricular topic addressed is the development of an ethical understanding of the scientific and technological issues of genetic engineering. 11 grade 8 students are studied as they proceed through 40 hours of curricular instruction based on the complex systems evolutionary framework. Results demonstrate growth in both complex systems thinking and content knowledge of the topic of genetic engineering. Several memetic processes are hypothesized to have influenced how and why ideas change. Categorized by factors influencing either reflective or non-reflective selection, these processes appear to have exerted differential effects on students' abilities to think and act in complex ways at various points throughout the study. Finally, an analysis of winner and loser memes is offered that is intended to reveal information about the conceptual system---its strengths and deficiencies---that can help educators assess curricular goals and organize and construct additional educational activities.

The complexity of cancer in multiple family members: dynamics of social work collaboration.

PubMed

Snow, Alison; Gilbertson, Kristen

2011-01-01

This article presents a case study of one family affected by a cancer diagnosis in both the father and the daughter, who were diagnosed within the same time interval and who underwent treatment at the same time. The article examines the relationship between the caregivers and the oncology patient as well as with one another when the stress of diagnosis is compounded by multiple, simultaneous, and similar diagnoses in a highly condensed period of time. A thorough examination of the literature reveals that there are significant gaps regarding how multiple cancer diagnoses in one family affect the family dynamic, individual and collective coping styles, and caregiver burden. The diagnoses can also dramatically exacerbate economic stressors in a family. The coordination of psychosocial care from the perspectives of the adult and pediatric oncology social workers at an urban academic medical center will be discussed. The social work role, importance of collaboration, and family centered care perspective will be discussed as a method of easing the treatment experience for families in psychosocial distress.

Dynamics of social behaviour at parturition in a gregarious ungulate.

PubMed

Pérez-Barbería, F J; Walker, D M

2018-05-01

Group living is the behavioural response that results when individuals assess the costs vs benefits of sociality, and these trade-offs vary across an animal's life. Here we quantitatively assess how periparturient condition (mother/non-mother) and births affect the dynamics of social interactions of a gregarious ungulate, and how such can help to explain evolutionary hypotheses of the mother-offspring bond. To achieve this we used data of the individual movement of a group of Scottish blackface sheep (Ovis aries) marked with GPS collars and properties of mathematical graphs (networks). Euclidean pair-wise distance between sheep were threshold at different percentiles to determine network links, and these thresholds have a profound effect on the connectivity of the resulting network. Births increased the average pair-wise distance between mothers, and between mothers and non-mothers, with less effect on the distance between non-mothers. Mothers occupied peripheral positions within the flock, more evident following births. Associations between individuals (i.e. network community change) were highly dynamic, though mothers were less likely to change community than non-mothers, especially after births. Births hampered individual communication within the flock (assessed via network closeness centrality), especially in mothers. Overall leadership (lead positioning relative to flock movement) was not associated to reproductive condition, and individual leadership rank was not affected by births. A ten minute GPS acquisition time was adequate to capture complex social dynamics in sheep movement. The results on mother's isolation behaviour support the hypotheses of selection for maternal imprint facilitation, reducing risks to nursing alien offspring, and group/multilevel selection on group formation. Copyright © 2018 Elsevier B.V. All rights reserved.

Fluctuations and Noise in Stochastic Spread of Respiratory Infection Epidemics in Social Networks

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Emelyanova, Natalya; Demin, Sergey; Gafarov, Fail; Hänggi, Peter; Yulmetyeva, Dinara

2003-05-01

For the analysis of epidemic and disease dynamics complexity, it is necessary to understand the basic principles and notions of its spreading in long-time memory media. Here we considering the problem from a theoretical and practical viewpoint, presenting the quantitative evidence confirming the existence of stochastic long-range memory and robust chaos in a real time series of respiratory infections of human upper respiratory track. In this work we present a new statistical method of analyzing the spread of grippe and acute respiratory track infections epidemic process of human upper respiratory track by means of the theory of discrete non-Markov stochastic processes. We use the results of our recent theory (Phys. Rev. E 65, 046107 (2002)) for the study of statistical effects of memory in real data series, describing the epidemic dynamics of human acute respiratory track infections and grippe. The obtained results testify to an opportunity of the strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks with a view to time discreteness and effects of statistical memory.

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants.

PubMed

Cruz-Garza, Jesus G; Hernandez, Zachery R; Tse, Teresa; Caducoy, Eunice; Abibullaev, Berdakh; Contreras-Vidal, Jose L

2015-10-04

Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental paradigms and analysis tools have been limited to constrained laboratory tasks and contexts due to technical limitations imposed by the available set of measuring and analysis techniques and the age of the subjects. These limitations severely limit the study of developmental neural dynamics and associated neural networks engaged in cognition, perception and action in infants performing "in action and in context". This protocol presents a novel approach to study infants and young children as they freely organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment. The proposed methodology integrates synchronized high-density active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. This setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.

Population and Environment

PubMed Central

de Sherbinin, Alex; Carr, David; Cassels, Susan; Jiang, Leiwen

2009-01-01

The interactions between human population dynamics and the environment have often been viewed mechanistically. This review elucidates the complexities and contextual specificities of population-environment relationships in a number of domains. It explores the ways in which demographers and other social scientists have sought to understand the relationships among a full range of population dynamics (e.g., population size, growth, density, age and sex composition, migration, urbanization, vital rates) and environmental changes. The chapter briefly reviews a number of the theories for understanding population and the environment and then proceeds to provide a state-of-the-art review of studies that have examined population dynamics and their relationship to five environmental issue areas. The review concludes by relating population-environment research to emerging work on human-environment systems. PMID:20011237

Moving sociohydrology forward: a synthesis across studies

NASA Astrophysics Data System (ADS)

Troy, T. J.; Konar, M.; Srinivasan, V.; Thompson, S.

2015-03-01

Sociohydrology is the study of coupled human-water systems with the premise that water and human systems co-evolve, often with two-way coupling. A recent special issue in HESS/ESD, "Predictions under change: water, earth, and biota in the Anthropocene", includes a number of sociohydrologic publications that allow for a survey of the current state of understanding of sociohydrology and the coupled system dynamics and feedbacks, the research methodologies available, and the norms and ethics involved in studying sociohydrologic systems. Although sociohydrology is concerned with coupled human-water systems, it is critical to consider the sociohydrologic system as embedded in a larger, complex social-ecological system through which human-water feedbacks can occur and from which the sociohydrologic system cannot be isolated. As such, sociohydrology can draw on tools developed in the social-ecological and complex systems literature to further our sociohydrologic knowledge, and this is identified as a ripe area of future research.

Linking disaster resilience and urban sustainability: a glocal approach for future cities.

PubMed

Asprone, Domenico; Manfredi, Gaetano

2015-01-01

Resilience and sustainability will be two primary objectives of future cities. The violent consequences of extreme natural events and the environmental, social and economic burden of contemporary cities make the concepts of resilience and sustainability extremely relevant. In this paper we analyse the various definitions of resilience and sustainability applied to urban systems and propose a synthesis, based on similarities between the two concepts. According to the proposed approach, catastrophic events and the subsequent transformations occurring in urban systems represent a moment in the city life cycle to be seen in terms of the complex sustainability framework. Hence, resilience is seen as a requirement for urban system sustainability. In addition, resilience should be evaluated not only for single cities, with their physical and social systems, but also on a global scale, taking into account the complex and dynamic relationships connecting contemporary cities. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Interacting opinion and disease dynamics in multiplex networks: Discontinuous phase transition and nonmonotonic consensus times

NASA Astrophysics Data System (ADS)

Velásquez-Rojas, Fátima; Vazquez, Federico

2017-05-01

Opinion formation and disease spreading are among the most studied dynamical processes on complex networks. In real societies, it is expected that these two processes depend on and affect each other. However, little is known about the effects of opinion dynamics over disease dynamics and vice versa, since most studies treat them separately. In this work we study the dynamics of the voter model for opinion formation intertwined with that of the contact process for disease spreading, in a population of agents that interact via two types of connections, social and contact. These two interacting dynamics take place on two layers of networks, coupled through a fraction q of links present in both networks. The probability that an agent updates its state depends on both the opinion and disease states of the interacting partner. We find that the opinion dynamics has striking consequences on the statistical properties of disease spreading. The most important is that the smooth (continuous) transition from a healthy to an endemic phase observed in the contact process, as the infection probability increases beyond a threshold, becomes abrupt (discontinuous) in the two-layer system. Therefore, disregarding the effects of social dynamics on epidemics propagation may lead to a misestimation of the real magnitude of the spreading. Also, an endemic-healthy discontinuous transition is found when the coupling q overcomes a threshold value. Furthermore, we show that the disease dynamics delays the opinion consensus, leading to a consensus time that varies nonmonotonically with q in a large range of the model's parameters. A mean-field approach reveals that the coupled dynamics of opinions and disease can be approximately described by the dynamics of the voter model decoupled from that of the contact process, with effective probabilities of opinion and disease transmission.

Assisted-living spaces for end-users with complex needs: a proposed implementation and delivery model.

PubMed

Linskell, Jeremy; Bouamrane, Matt-Mouley

2012-09-01

An assisted living space (ALS) is a technology-enabled environment designed to allow people with complex health or social care needs to remain, and live independently, in their own home for longer. However, many challenges remain in order to deliver usable systems acceptable to a diverse range of stakeholders, including end-users, and their families and carers, as well as health and social care services. ALSs need to support activities of daily-living while allowing end-users to maintain important social connections. They must be dynamic, flexible and adaptable living environments. In this article, we provide an overview of the technological landscape of assisted-living technology (ALT) and recent policies to promote an increased adoption of ALT in Scotland. We discuss our experiences in implementing technology-supported ALSs and emphasise key lessons. Finally, we propose an iterative and pragmatic user-centred implementation model for delivering ALSs in complex-needs scenarios. This empirical model is derived from our past ALS implementations. The proposed model allows project stakeholders to identify requirements, allocate tasks and responsibilities, and identify appropriate technological solutions for the delivery of functional ALS systems. The model is generic and makes no assumptions on needs or technology solutions, nor on the technical knowledge, skills and experience of the stakeholders involved in the ALS design process.

Epidemic processes in complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

2015-07-01

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

Spreading dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pei, Sen; Makse, Hernán A.

2013-12-01

Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

Place knowing of persons and populations: restoring the place work of nursing.

PubMed

Thomas, Elizabeth A

2013-12-01

Place emerges when space acquires definition in social constructions of meaning as landscape-languages, which reflect assumptions about physical and social realities. The place work of nursing, which resonated throughout Nightingale's work and the profession's evolution, focuses on human health and healing in the historical transitions and landscape-languages of populations. However, evidence-based practice dominated by empirical knowing inadequately addresses complex health and illness dynamics between place and populations. Translating evidence to the life course experiences of individuals and populations requires place knowing of human situated embodiment within discrete space. An exploration of the concept of place, its application to nursing, and the need for a place paradigm for practice is presented. A sense of salience and situated cognition has been identified as the essential element of the transformation needed in the education of nurses. Place knowing integrates other patterns of knowing (empirical, ethical, aesthetical, personal, unknowing, sociopolitical, and emancipatory) in a situated cognition. Place knowing, like other established patterns of knowing, is a significant epistemological foundation of nursing. Place knowing allows the nuanced intricately complex dynamics of embodied situated human health and illness to be examined, the salience of the particulars to be considered, and the whole of the landscape-languages to emerge.

Fluctuations in Wikipedia access-rate and edit-event data

NASA Astrophysics Data System (ADS)

Kämpf, Mirko; Tismer, Sebastian; Kantelhardt, Jan W.; Muchnik, Lev

2012-12-01

Internet-based social networks often reflect extreme events in nature and society by drastic increases in user activity. We study and compare the dynamics of the two major complex processes necessary for information spread via the online encyclopedia ‘Wikipedia’, i.e., article editing (information upload) and article access (information viewing) based on article edit-event time series and (hourly) user access-rate time series for all articles. Daily and weekly activity patterns occur in addition to fluctuations and bursting activity. The bursts (i.e., significant increases in activity for an extended period of time) are characterized by a power-law distribution of durations of increases and decreases. For describing the recurrence and clustering of bursts we investigate the statistics of the return intervals between them. We find stretched exponential distributions of return intervals in access-rate time series, while edit-event time series yield simple exponential distributions. To characterize the fluctuation behavior we apply detrended fluctuation analysis (DFA), finding that most article access-rate time series are characterized by strong long-term correlations with fluctuation exponents α≈0.9. The results indicate significant differences in the dynamics of information upload and access and help in understanding the complex process of collecting, processing, validating, and distributing information in self-organized social networks.

Interactional dynamics of same-sex marriage legislation in the United States

PubMed Central

2017-01-01

Understanding how people form opinions and make decisions is a complex phenomenon that depends on both personal practices and interactions. Recent availability of real-world data has enabled quantitative analysis of opinion formation, which illuminates phenomena that impact physical and social sciences. Public policies exemplify complex opinion formation spanning individual and population scales, and a timely example is the legalization of same-sex marriage in the United States. Here, we seek to understand how this issue captures the relationship between state-laws and Senate representatives subject to geographical and ideological factors. Using distance-based correlations, we study how physical proximity and state-government ideology may be used to extract patterns in state-law adoption and senatorial support of same-sex marriage. Results demonstrate that proximal states have similar opinion dynamics in both state-laws and senators’ opinions, and states with similar state-government ideology have analogous senators’ opinions. Moreover, senators’ opinions drive state-laws with a time lag. Thus, change in opinion not only results from negotiations among individuals, but also reflects inherent spatial and political similarities and temporal delays. We build a social impact model of state-law adoption in light of these results, which predicts the evolution of state-laws legalizing same-sex marriage over the last three decades. PMID:28680669

Interactional dynamics of same-sex marriage legislation in the United States.

PubMed

Roy, Subhradeep; Abaid, Nicole

2017-06-01

Understanding how people form opinions and make decisions is a complex phenomenon that depends on both personal practices and interactions. Recent availability of real-world data has enabled quantitative analysis of opinion formation, which illuminates phenomena that impact physical and social sciences. Public policies exemplify complex opinion formation spanning individual and population scales, and a timely example is the legalization of same-sex marriage in the United States. Here, we seek to understand how this issue captures the relationship between state-laws and Senate representatives subject to geographical and ideological factors. Using distance-based correlations, we study how physical proximity and state-government ideology may be used to extract patterns in state-law adoption and senatorial support of same-sex marriage. Results demonstrate that proximal states have similar opinion dynamics in both state-laws and senators' opinions, and states with similar state-government ideology have analogous senators' opinions. Moreover, senators' opinions drive state-laws with a time lag. Thus, change in opinion not only results from negotiations among individuals, but also reflects inherent spatial and political similarities and temporal delays. We build a social impact model of state-law adoption in light of these results, which predicts the evolution of state-laws legalizing same-sex marriage over the last three decades.

Experimentally induced innovations lead to persistent culture via conformity in wild birds

PubMed Central

Aplin, L.M.; Farine, D.R.; Morand-Ferron, J.; Cockburn, A.; Thornton, A.; Sheldon, B.C.

2014-01-01

In human societies, cultural norms arise when behaviours are transmitted with high-fidelity social learning through social networks1. However a paucity of experimental studies has meant that there is no comparable understanding of the process by which socially transmitted behaviours may spread and persist in animal populations2,3. Here, we introduce alternative novel foraging techniques into replicated wild sub-populations of great tits (Parus major), and employ automated tracking to map the diffusion, establishment and long-term persistence of seeded behaviours. We further use social network analysis to examine social factors influencing diffusion dynamics. From just two trained birds in each sub-population, information spread rapidly through social network ties to reach an average of 75% of individuals, with 508 knowledgeable individuals performing 58,975 solutions. Sub-populations were heavily biased towards the technique originally introduced, resulting in established local arbitrary traditions that were stable over two generations, despite high population turnover. Finally, we demonstrate a strong effect of social conformity, with individuals disproportionately adopting the most frequent local variant when first learning, but then also continuing to favour social over personal information by matching their technique to the majority variant. Cultural conformity is thought to be a key factor in the evolution of complex culture in humans4-7. In providing the first experimental demonstration of conformity in a wild non-primate, and of cultural norms in foraging techniques in any wild animal, our results suggest a much wider evolutionary occurrence of such apparently complex cultural behaviour. PMID:25470065

Structure-based control of complex networks with nonlinear dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Yang, Gang; Albert, Reka

What can we learn about controlling a system solely from its underlying network structure? Here we use a framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors, regardless of the dynamic details and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of classical structural control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case, but not in specific model instances. This work was supported by NSF Grants PHY 1205840 and IIS 1160995. JGTZ is a recipient of a Stand Up To Cancer - The V Foundation Convergence Scholar Award.

Maximizing information exchange between complex networks

NASA Astrophysics Data System (ADS)

West, Bruce J.; Geneston, Elvis L.; Grigolini, Paolo

2008-10-01

Science is not merely the smooth progressive interaction of hypothesis, experiment and theory, although it sometimes has that form. More realistically the scientific study of any given complex phenomenon generates a number of explanations, from a variety of perspectives, that eventually requires synthesis to achieve a deep level of insight and understanding. One such synthesis has created the field of out-of-equilibrium statistical physics as applied to the understanding of complex dynamic networks. Over the past forty years the concept of complexity has undergone a metamorphosis. Complexity was originally seen as a consequence of memory in individual particle trajectories, in full agreement with a Hamiltonian picture of microscopic dynamics and, in principle, macroscopic dynamics could be derived from the microscopic Hamiltonian picture. The main difficulty in deriving macroscopic dynamics from microscopic dynamics is the need to take into account the actions of a very large number of components. The existence of events such as abrupt jumps, considered by the conventional continuous time random walk approach to describing complexity was never perceived as conflicting with the Hamiltonian view. Herein we review many of the reasons why this traditional Hamiltonian view of complexity is unsatisfactory. We show that as a result of technological advances, which make the observation of single elementary events possible, the definition of complexity has shifted from the conventional memory concept towards the action of non-Poisson renewal events. We show that the observation of crucial processes, such as the intermittent fluorescence of blinking quantum dots as well as the brain’s response to music, as monitored by a set of electrodes attached to the scalp, has forced investigators to go beyond the traditional concept of complexity and to establish closer contact with the nascent field of complex networks. Complex networks form one of the most challenging areas of modern research overarching all of the traditional scientific disciplines. The transportation networks of planes, highways and railroads; the economic networks of global finance and stock markets; the social networks of terrorism, governments, businesses and churches; the physical networks of telephones, the Internet, earthquakes and global warming and the biological networks of gene regulation, the human body, clusters of neurons and food webs, share a number of apparently universal properties as the networks become increasingly complex. Ubiquitous aspects of such complex networks are the appearance of non-stationary and non-ergodic statistical processes and inverse power-law statistical distributions. Herein we review the traditional dynamical and phase-space methods for modeling such networks as their complexity increases and focus on the limitations of these procedures in explaining complex networks. Of course we will not be able to review the entire nascent field of network science, so we limit ourselves to a review of how certain complexity barriers have been surmounted using newly applied theoretical concepts such as aging, renewal, non-ergodic statistics and the fractional calculus. One emphasis of this review is information transport between complex networks, which requires a fundamental change in perception that we express as a transition from the familiar stochastic resonance to the new concept of complexity matching.

Unifying Complexity and Information

NASA Astrophysics Data System (ADS)

Ke, Da-Guan

2013-04-01

Complex systems, arising in many contexts in the computer, life, social, and physical sciences, have not shared a generally-accepted complexity measure playing a fundamental role as the Shannon entropy H in statistical mechanics. Superficially-conflicting criteria of complexity measurement, i.e. complexity-randomness (C-R) relations, have given rise to a special measure intrinsically adaptable to more than one criterion. However, deep causes of the conflict and the adaptability are not much clear. Here I trace the root of each representative or adaptable measure to its particular universal data-generating or -regenerating model (UDGM or UDRM). A representative measure for deterministic dynamical systems is found as a counterpart of the H for random process, clearly redefining the boundary of different criteria. And a specific UDRM achieving the intrinsic adaptability enables a general information measure that ultimately solves all major disputes. This work encourages a single framework coving deterministic systems, statistical mechanics and real-world living organisms.

Punctuated equilibrium dynamics in human communications

NASA Astrophysics Data System (ADS)

Peng, Dan; Han, Xiao-Pu; Wei, Zong-Wen; Wang, Bing-Hong

2015-10-01

A minimal model based on network incorporating individual interactions is proposed to study the non-Poisson statistical properties of human behavior: individuals in system interact with their neighbors, the probability of an individual acting correlates to its activity, and all the individuals involved in action will change their activities randomly. The model reproduces varieties of spatial-temporal patterns observed in empirical studies of human daily communications, providing insight into various human activities and embracing a range of realistic social interacting systems, particularly, intriguing bimodal phenomenon. This model bridges priority queueing theory and punctuated equilibrium dynamics, and our modeling and analysis is likely to shed light on non-Poisson phenomena in many complex systems.

Expected Number of Fixed Points in Boolean Networks with Arbitrary Topology.

PubMed

Mori, Fumito; Mochizuki, Atsushi

2017-07-14

Boolean network models describe genetic, neural, and social dynamics in complex networks, where the dynamics depend generally on network topology. Fixed points in a genetic regulatory network are typically considered to correspond to cell types in an organism. We prove that the expected number of fixed points in a Boolean network, with Boolean functions drawn from probability distributions that are not required to be uniform or identical, is one, and is independent of network topology if only a feedback arc set satisfies a stochastic neutrality condition. We also demonstrate that the expected number is increased by the predominance of positive feedback in a cycle.

Systems thinking in combating infectious diseases.

PubMed

Xia, Shang; Zhou, Xiao-Nong; Liu, Jiming

2017-09-11

The transmission of infectious diseases is a dynamic process determined by multiple factors originating from disease pathogens and/or parasites, vector species, and human populations. These factors interact with each other and demonstrate the intrinsic mechanisms of the disease transmission temporally, spatially, and socially. In this article, we provide a comprehensive perspective, named as systems thinking, for investigating disease dynamics and associated impact factors, by means of emphasizing the entirety of a system's components and the complexity of their interrelated behaviors. We further develop the general steps for performing systems approach to tackling infectious diseases in the real-world settings, so as to expand our abilities to understand, predict, and mitigate infectious diseases.

Social, Environmental, and Health Vulnerability to Climate Change: The Case of the Municipalities of Minas Gerais, Brazil.

PubMed

Quintão, Ana Flávia; Brito, Isabela; Oliveira, Frederico; Madureira, Ana Paula; Confalonieri, Ulisses

2017-01-01

Vulnerability to climate change is a complex and dynamic phenomenon involving both social and physical/environmental aspects. It is presented as a method for the quantification of the vulnerability of all municipalities of Minas Gerais, a state in southeastern Brazil. It is based on the aggregation of different kinds of environmental, climatic, social, institutional, and epidemiological variables, to form a composite index. This was named "Index of Human Vulnerability" and was calculated using a software (SisVuClima®) specifically developed for this purpose. Social, environmental, and health data were combined with the climatic scenarios RCP 4.5 and 8.5, downscaled from ETA-HadGEM2-ES for each municipality. The Index of Human Vulnerability associated with the RCP 8.5 has shown a higher vulnerability for municipalities in the southern and eastern parts of the state of Minas Gerais.

Social, Environmental, and Health Vulnerability to Climate Change: The Case of the Municipalities of Minas Gerais, Brazil

PubMed Central

Brito, Isabela; Oliveira, Frederico; Madureira, Ana Paula

2017-01-01

Vulnerability to climate change is a complex and dynamic phenomenon involving both social and physical/environmental aspects. It is presented as a method for the quantification of the vulnerability of all municipalities of Minas Gerais, a state in southeastern Brazil. It is based on the aggregation of different kinds of environmental, climatic, social, institutional, and epidemiological variables, to form a composite index. This was named “Index of Human Vulnerability” and was calculated using a software (SisVuClima®) specifically developed for this purpose. Social, environmental, and health data were combined with the climatic scenarios RCP 4.5 and 8.5, downscaled from ETA-HadGEM2-ES for each municipality. The Index of Human Vulnerability associated with the RCP 8.5 has shown a higher vulnerability for municipalities in the southern and eastern parts of the state of Minas Gerais. PMID:28465693

Transformative environmental governance

USGS Publications Warehouse

Chaffin, Brian C.; Garmestani, Ahjond S.; Gunderson, Lance H.; Harm Benson, Melinda; Angeler, David G.; Arnold, Craig Anthony (Tony); Cosens, Barbara; Kundis Craig, Robin; Ruhl, J.B.; Allen, Craig R.

2016-01-01

Transformative governance is an approach to environmental governance that has the capacity to respond to, manage, and trigger regime shifts in coupled social-ecological systems (SESs) at multiple scales. The goal of transformative governance is to actively shift degraded SESs to alternative, more desirable, or more functional regimes by altering the structures and processes that define the system. Transformative governance is rooted in ecological theories to explain cross-scale dynamics in complex systems, as well as social theories of change, innovation, and technological transformation. Similar to adaptive governance, transformative governance involves a broad set of governance components, but requires additional capacity to foster new social-ecological regimes including increased risk tolerance, significant systemic investment, and restructured economies and power relations. Transformative governance has the potential to actively respond to regime shifts triggered by climate change, and thus future research should focus on identifying system drivers and leading indicators associated with social-ecological thresholds.

Computational Social Science: Exciting Progress and Future Challenges

NASA Astrophysics Data System (ADS)

Watts, Duncan

The past 15 years have witnessed a remarkable increase in both the scale and scope of social and behavioral data available to researchers, leading some to herald the emergence of a new field: ``computational social science.'' Against these exciting developments stands a stubborn fact: that in spite of many thousands of published papers, there has been surprisingly little progress on the ``big'' questions that motivated the field in the first place--questions concerning systemic risk in financial systems, problem solving in complex organizations, and the dynamics of epidemics or social movements, among others. In this talk I highlight some examples of research that would not have been possible just a handful of years ago and that illustrate the promise of CSS. At the same time, they illustrate its limitations. I then conclude with some thoughts on how CSS can bridge the gap between its current state and its potential.

Conceptualizing the dynamics of workplace stress: a systems-based study of nursing aides.

PubMed

Jetha, Arif; Kernan, Laura; Kurowski, Alicia

2017-01-05

Workplace stress is a complex phenomenon that may often be dynamic and evolving over time. Traditional linear modeling does not allow representation of recursive feedback loops among the implicated factors. The objective of this study was to develop a multidimensional system dynamics model (SDM) of workplace stress among nursing aides and conduct simulations to illustrate how changes in psychosocial perceptions and workplace factors might influence workplace stress over time. Eight key informants with prior experience in a large study of US nursing home workers participated in model building. Participants brainstormed the range of components related to workplace stress. Components were grouped together based on common themes and translated into feedback loops. The SDM was parameterized through key informant insight on the shape and magnitude of the relationship between model components. Model construction was also supported utilizing survey data collected as part of the larger study. All data was entered into the software program, Vensim. Simulations were conducted to examine how adaptations to model components would influence workplace stress. The SDM included perceptions of organizational conditions (e.g., job demands and job control), workplace social support (i.e., managerial and coworker social support), workplace safety, and demands outside of work (i.e. work-family conflict). Each component was part of a reinforcing feedback loop. Simulations exhibited that scenarios with increasing job control and decreasing job demands led to a decline in workplace stress. Within the context of the system, the effects of workplace social support, workplace safety, and work-family conflict were relatively minor. SDM methodology offers a unique perspective for researchers and practitioners to view workplace stress as a dynamic process. The portrayal of multiple recursive feedback loops can guide the development of policies and programs within complex organizational contexts with attention both to interactions among causes and avoidance of adverse unintended consequences. While additional research is needed to further test the modeling approach, findings might underscore the need to direct workplace interventions towards changing organizational conditions for nursing aides.

Early social communication in infants with fragile X syndrome and infant siblings of children with autism spectrum disorder.

PubMed

Hahn, Laura J; Brady, Nancy C; McCary, Lindsay; Rague, Lisa; Roberts, Jane E

2017-12-01

Little research in fragile X syndrome (FXS) has prospectively examined early social communication. To compare early social communication in infants with FXS, infant siblings of children with autism spectrum disorder (ASIBs), and typically developing (TD) infants. Participants were 18 infants with FXS, 21 ASIBs, and 22 TD infants between 7.5-14.5 months. Social communication was coded using the Communication Complexity Scale during the administration of Autism Observation Scale for Infants. Descriptively different patterns were seen across the three groups. Overall infants with FXS had lower social communication than ASIBs or TD infants when controlling for nonverbal cognitive abilities. However, infants with FXS had similar levels of social communication as ASIBs or TD infants during peek-a-boo. No differences were observed between ASIBs and TD infants. For all infants, higher social communication was related to lower ASD risk. Findings provide insight into the developmental course of social communication in FXS. The dynamic nature of social games may help to stimulate communication in infants with FXS. Language interventions with a strong social component may be particularly effective for promoting language development in FXS. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic phenomena and human activity in an artificial society

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kruszewska, N.; Kosiński, R. A.

2008-12-01

We study dynamic phenomena in a large social network of nearly 3×104 individuals who interact in the large virtual world of a massive multiplayer online role playing game. On the basis of a database received from the online game server, we examine the structure of the friendship network and human dynamics. To investigate the relation between networks of acquaintances in virtual and real worlds, we carried out a survey among the players. We show that, even though the virtual network did not develop as a growing graph of an underlying network of social acquaintances in the real world, it influences it. Furthermore we find very interesting scaling laws concerning human dynamics. Our research shows how long people are interested in a single task and how much time they devote to it. Surprisingly, exponent values in both cases are close to -1 . We calculate the activity of individuals, i.e., the relative time daily devoted to interactions with others in the artificial society. Our research shows that the distribution of activity is not uniform and is highly correlated with the degree of the node, and that such human activity has a significant influence on dynamic phenomena, e.g., epidemic spreading and rumor propagation, in complex networks. We find that spreading is accelerated (an epidemic) or decelerated (a rumor) as a result of superspreaders’ various behavior.

Rapid identifying high-influence nodes in complex networks

NASA Astrophysics Data System (ADS)

Song, Bo; Jiang, Guo-Ping; Song, Yu-Rong; Xia, Ling-Ling

2015-10-01

A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying method (RIM) to find the fraction of high-influential nodes. Instead of ranking all nodes, our method only aims at ranking a small number of nodes in network. We set the high-influential nodes as initial spreaders, and evaluate the performance of RIM by the susceptible-infected-recovered (SIR) model. The simulations show that in different networks, RIM performs well on rapid identifying high-influential nodes, which is verified by typical ranking methods, such as degree, closeness, betweenness, and eigenvector centrality methods. Project supported by the National Natural Science Foundation of China (Grant Nos. 61374180 and 61373136), the Ministry of Education Research in the Humanities and Social Sciences Planning Fund Project, China (Grant No. 12YJAZH120), and the Six Projects Sponsoring Talent Summits of Jiangsu Province, China (Grant No. RLD201212).

Physiological mechanisms underlying animal social behaviour.

PubMed

Seebacher, Frank; Krause, Jens

2017-08-19

Many species of animal live in groups, and the group represents the organizational level within which ecological and evolutionary processes occur. Understanding these processes, therefore, relies on knowledge of the mechanisms that permit or constrain group formation. We suggest that physiological capacities and differences in physiology between individuals modify fission-fusion dynamics. Differences between individuals in locomotor capacity and metabolism may lead to fission of groups and sorting of individuals into groups with similar physiological phenotypes. Environmental impacts such as hypoxia can influence maximum group sizes and structure in fish schools by altering access to oxygenated water. The nutritional environment determines group cohesion, and the increase in information collected by the group means that individuals should rely more on social information and form more cohesive groups in uncertain environments. Changing environmental contexts require rapid responses by individuals to maintain group coordination, which are mediated by neuroendocrine signalling systems such as nonapeptides and steroid hormones. Brain processing capacity may constrain social complexity by limiting information processing. Failure to evaluate socially relevant information correctly limits social interactions, which is seen, for example, in autism. Hence, functioning of a group relies to a large extent on the perception and appropriate processing of signals from conspecifics. Many if not all physiological systems are mechanistically linked, and therefore have synergistic effects on social behaviour. A challenge for the future lies in understanding these interactive effects, which will improve understanding of group dynamics, particularly in changing environments.This article is part of the themed issue 'Physiological determinants of social behaviour in animals'. © 2017 The Author(s).

Physiological mechanisms underlying animal social behaviour

PubMed Central

2017-01-01

Many species of animal live in groups, and the group represents the organizational level within which ecological and evolutionary processes occur. Understanding these processes, therefore, relies on knowledge of the mechanisms that permit or constrain group formation. We suggest that physiological capacities and differences in physiology between individuals modify fission–fusion dynamics. Differences between individuals in locomotor capacity and metabolism may lead to fission of groups and sorting of individuals into groups with similar physiological phenotypes. Environmental impacts such as hypoxia can influence maximum group sizes and structure in fish schools by altering access to oxygenated water. The nutritional environment determines group cohesion, and the increase in information collected by the group means that individuals should rely more on social information and form more cohesive groups in uncertain environments. Changing environmental contexts require rapid responses by individuals to maintain group coordination, which are mediated by neuroendocrine signalling systems such as nonapeptides and steroid hormones. Brain processing capacity may constrain social complexity by limiting information processing. Failure to evaluate socially relevant information correctly limits social interactions, which is seen, for example, in autism. Hence, functioning of a group relies to a large extent on the perception and appropriate processing of signals from conspecifics. Many if not all physiological systems are mechanistically linked, and therefore have synergistic effects on social behaviour. A challenge for the future lies in understanding these interactive effects, which will improve understanding of group dynamics, particularly in changing environments. This article is part of the themed issue ‘Physiological determinants of social behaviour in animals’. PMID:28673909

Fashion cycle dynamics in a model with endogenous discrete evolution of heterogeneous preferences

NASA Astrophysics Data System (ADS)

Naimzada, A. K.; Pireddu, M.

2018-05-01

We propose a discrete-time exchange economy evolutionary model, in which two groups of agents are characterized by different preference structures. The reproduction level of a group is related to its attractiveness degree, which depends on the social visibility level, determined by the consumption choices of the agents in that group. The attractiveness of a group is initially increasing with its visibility level, but it becomes decreasing when its visibility exceeds a given threshold value, due to a congestion effect. Thanks to the combined action of the price mechanism and of the share updating rule, the model is able to reproduce the recurrent dynamic behavior typical of the fashion cycle, presenting booms and busts both in the agents' consumption choices and in the population shares. More precisely, we investigate the existence of equilibria and their stability, and we perform a qualitative bifurcation analysis on varying the parameter describing the group's heterogeneity degree. From a global viewpoint, we detect, among others, multistability phenomena in which the group coexistence is dynamic, either regular or irregular, and the fashion cycle occurs. The existence of complex dynamics is proven via the method of the turbulent maps, working with homoclinic orbits. Finally, we provide a social and economic interpretation of the main scenarios.

Providing health services during a civil war: the experience of a garrison town in South Sudan.

PubMed

Kevlihan, Rob

2013-10-01

The impact of conflict, particularly conflict arising during civil wars, on the provision of healthcare is a subject that has not been widely considered in conflict-related research. Combatants often target health services to weaken or to defeat the enemy, while attempts to maintain or improve health systems also can comprise part of counter-insurgency 'hearts-and-minds' strategies. This paper describes the dynamics associated with the provision of health services in Malakal, an important garrison town in South Sudan, during the second Sudanese civil war (1983-2005). Drawing on the concepts of opportunity hoarding and exploitation, it explores the social and political dynamics of service provision in and around the town during the war. These concepts provide a useful lens with which to understand better how health services are affected by conflict, while the empirical case study presented in the paper illustrates dynamics that may be repeated in other contexts. The concepts and case study set out in this paper should prove useful to healthcare providers working in conflict zones, including humanitarian aid agencies and their employees, increasing their understanding of the social and political dynamics that they are likely to face during future conflict-related complex emergencies. © 2013 The Author(s). Disasters © Overseas Development Institute, 2013.

Fashion cycle dynamics in a model with endogenous discrete evolution of heterogeneous preferences.

PubMed

Naimzada, A K; Pireddu, M

2018-05-01

We propose a discrete-time exchange economy evolutionary model, in which two groups of agents are characterized by different preference structures. The reproduction level of a group is related to its attractiveness degree, which depends on the social visibility level, determined by the consumption choices of the agents in that group. The attractiveness of a group is initially increasing with its visibility level, but it becomes decreasing when its visibility exceeds a given threshold value, due to a congestion effect. Thanks to the combined action of the price mechanism and of the share updating rule, the model is able to reproduce the recurrent dynamic behavior typical of the fashion cycle, presenting booms and busts both in the agents' consumption choices and in the population shares. More precisely, we investigate the existence of equilibria and their stability, and we perform a qualitative bifurcation analysis on varying the parameter describing the group's heterogeneity degree. From a global viewpoint, we detect, among others, multistability phenomena in which the group coexistence is dynamic, either regular or irregular, and the fashion cycle occurs. The existence of complex dynamics is proven via the method of the turbulent maps, working with homoclinic orbits. Finally, we provide a social and economic interpretation of the main scenarios.

[The dynamics of heath indicators of population of industrial town].

PubMed

Kalinkin, D E; Karpov, A B; Takhauov, R M; Samoĭlova, Iu A

2013-01-01

The article presents the results of analysis of dynamics of health indicators of population of industrial town (medical demographic indicators, disability, morbidity of social hygienically important diseases) during 1970-2010. The classified administrative territorial municipality of Seversk constructed near the Siberian chemical industrial center, the internationally first-rate complex of nuclear industry enterprises was used as a research base. It is demonstrated that dynamics of health indicators of studied population had such negative tendencies as rapid population ageing, population loss due to decrease of natality and increase of mortality (population of able-bodied age included), prevalence of cardio-vascular diseases, malignant neoplasms and external causes, chronization of diseases. The established tendencies are to be considered in management decision making targeted to support and promote population health in industrial towns.

Organizational Strategy and Business Environment Effects Based on a Computation Method

NASA Astrophysics Data System (ADS)

Reklitis, Panagiotis; Konstantopoulos, Nikolaos; Trivellas, Panagiotis

2007-12-01

According to many researchers of organizational theory, a great number of problems encountered by the manufacturing firms are due to their ineffectiveness to respond to significant changes of their external environment and align their competitive strategy accordingly. From this point of view, the pursuit of the appropriate generic strategy is vital for firms facing a dynamic and highly competitive environment. In the present paper, we adopt Porter's typology to operationalise organizational strategy (cost leadership, innovative and marketing differentiation, and focus) considering changes in the external business environment (dynamism, complexity and munificence). Although simulation of social events is a quite difficult task, since there are so many considerations (not all well understood) involved, in the present study we developed a dynamic system based on the conceptual framework of strategy-environment associations.

EvoGraph: On-The-Fly Efficient Mining of Evolving Graphs on GPU

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Song, Shuaiwen

With the prevalence of the World Wide Web and social networks, there has been a growing interest in high performance analytics for constantly-evolving dynamic graphs. Modern GPUs provide massive AQ1 amount of parallelism for efficient graph processing, but the challenges remain due to their lack of support for the near real-time streaming nature of dynamic graphs. Specifically, due to the current high volume and velocity of graph data combined with the complexity of user queries, traditional processing methods by first storing the updates and then repeatedly running static graph analytics on a sequence of versions or snapshots are deemed undesirablemore » and computational infeasible on GPU. We present EvoGraph, a highly efficient and scalable GPU- based dynamic graph analytics framework.« less

Promoting community socio-ecological sustainability through technology: A case study from Chile

NASA Astrophysics Data System (ADS)

Aguayo, Claudio; Eames, Chris

2017-12-01

The importance of community learning in effecting social change towards ecological sustainability has been recognised for some time. More recently, the use of Information and Communication Technology (ICT) tools to promote socio-ecological sustainability has been shown to have potential in community education for sustainable development (ESD). The effective design and use of technology for community learning implies an understanding of a range of cross-dimensional factors including: socio-cultural characteristics and needs of the target audience; considerations of available and culturally responsive types of technology; and non-formal pedagogical ESD strategies for community empowerment. In addition, both technology itself and social communities are dynamically evolving and complex entities. This article presents a case study which evaluated the potential of ICT for promoting ecological literacy and action competence amongst community members in southern Chile. The case study addressed the ecological deterioration of a lake, which is having deep social, economic, recreational and cultural implications locally. The authors' research involved developing a theoretical framework for the design, implementation and use of ICT for community learning for sustainability. The framework was based on key ideas from ESD, ICT and community education, and was underpinned by a systems thinking approach to account for the dynamism and complexity of such settings. Activity theory provided a frame to address overarching socio-cultural elements when using technology as a mediating tool for community learning. The authors' findings suggest that the use of an ICT tool, such as a website, can enhance ecological literacy in relation to a local socio-ecological issue.

Flexible social organization and high incidence of drifting in the sweat bee, Halictus scabiosae.

PubMed

Ulrich, Yuko; Perrin, Nicolas; Chapuisat, Michel

2009-04-01

The very diverse social systems of sweat bees make them interesting models to study social evolution. Here we focus on the dispersal behaviour and social organization of Halictus scabiosae, a common yet poorly known species of Europe. By combining field observations and genetic data, we show that females have multiple reproductive strategies, which generates a large diversity in the social structure of nests. A detailed microsatellite analysis of 60 nests revealed that 55% of the nests contained the offspring of a single female, whereas the rest had more complex social structures, with three clear cases of multiple females reproducing in the same nest and frequent occurrence of unrelated individuals. Drifting among nests was surprisingly common, as 16% of the 122 nests in the overall sample and 44% of the nests with complex social structure contained females that had genotypes consistent with being full-sisters of females sampled in other nests of the population. Drifters originated from nests with an above-average productivity and were unrelated to their nestmates, suggesting that drifting might be a strategy to avoid competition among related females. The sex-specific comparison of genetic differentiation indicated that dispersal was male-biased, which would reinforce local resource competition among females. The pattern of genetic differentiation among populations was consistent with a dynamic process of patch colonization and extinction, as expected from the unstable, anthropogenic habitat of this species. Overall, our data show that H. scabiosae varies greatly in dispersal behaviour and social organization. The surprisingly high frequency of drifters echoes recent findings in wasps and bees, calling for further investigation of the adaptive basis of drifting in the social insects.

Threat processing in generalized social phobia: an investigation of interpretation biases in ambiguous facial affect.

PubMed

Jusyte, Aiste; Schönenberg, Michael

2014-06-30

Facial affect is one of the most important information sources during the course of social interactions, but it is susceptible to distortion due to the complex and dynamic nature. Socially anxious individuals have been shown to exhibit alterations in the processing of social information, such as an attentional and interpretative bias toward threatening information. This may be one of the key factors contributing to the development and maintenance of anxious psychopathology. The aim of the current study was to investigate whether a threat-related interpretation bias is evident for ambiguous facial stimuli in a population of individuals with a generalized Social Anxiety Disorder (gSAD) as compared to healthy controls. Participants judged ambiguous happy/fearful, angry/fearful and angry/happy blends varying in intensity and rated the predominant affective expression. The results obtained in this study do not indicate that gSAD is associated with a biased interpretation of ambiguous facial affect. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Stylized facts in social networks: Community-based static modeling

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Murase, Yohsuke; Török, János; Kertész, János; Kaski, Kimmo

2018-06-01

The past analyses of datasets of social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Since the understanding of the structure of these complex social networks is far from complete, for deeper insight into human society more comprehensive datasets and modeling of the stylized facts are needed. Although the existing dynamical and static models can generate some stylized facts, here we take an alternative approach by devising a community-based static model with heterogeneous community sizes and larger communities having smaller link density and weight. With these few assumptions we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, as demonstrated numerically and analytically. Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications.

Essentialism, historical construction, and social influence: representations of Pomakness in majority talk in Western Thrace (Greece).

PubMed

Figgou, Lia

2013-12-01

Social psychological research has been particularly interested to study essentialism in the construction of social categories and to manifest its potential consequences in intergroup attitudes. Drawing upon this literature, the present study focuses on the argumentative resources employed to construct ethnic categories in a specific rhetorical context: focus group discussions between majority Greek educators about the minority group of Pomaks, historically residing in Western Thrace (Greece). Discussions were framed as an attempt to capture the particularities of minority education and data were analysed by the use of tools and concepts of discursive and rhetorical psychology. Analysis indicates that participants have multiple and complex recourses available to construct Pomakness. Representations of Pomakness as an essential a-historical entity coexist with conceptions of category membership and identification as a result of certain historical conditions and processes of social influence. Essential and de-essential category constructions are approached as rhetorically situated, oriented towards specific rhetorical ends in specific argumentative contexts. They are also considered, however, to be nested within a complex and dynamic intergroup context which reflects the ideological contradictions of the Greek policy towards the minority and which constitutes (but it is also reconstituted by) shifting group definitions and boundaries. © 2012 The British Psychological Society.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Social-ecological resilience and geomorphic systems

NASA Astrophysics Data System (ADS)

Chaffin, Brian C.; Scown, Murray

2018-03-01

Governance of coupled social-ecological systems (SESs) and the underlying geomorphic processes that structure and alter Earth's surface is a key challenge for global sustainability amid the increasing uncertainty and change that defines the Anthropocene. Social-ecological resilience as a concept of scientific inquiry has contributed to new understandings of the dynamics of change in SESs, increasing our ability to contextualize and implement governance in these systems. Often, however, the importance of geomorphic change and geomorphological knowledge is somewhat missing from processes employed to inform SES governance. In this contribution, we argue that geomorphology and social-ecological resilience research should be integrated to improve governance toward sustainability. We first provide definitions of engineering, ecological, community, and social-ecological resilience and then explore the use of these concepts within and alongside geomorphology in the literature. While ecological studies often consider geomorphology as an important factor influencing the resilience of ecosystems and geomorphological studies often consider the engineering resilience of geomorphic systems of interest, very few studies define and employ a social-ecological resilience framing and explicitly link the concept to geomorphic systems. We present five key concepts-scale, feedbacks, state or regime, thresholds and regime shifts, and humans as part of the system-which we believe can help explicitly link important aspects of social-ecological resilience inquiry and geomorphological inquiry in order to strengthen the impact of both lines of research. Finally, we discuss how these five concepts might be used to integrate social-ecological resilience and geomorphology to better understand change in, and inform governance of, SESs. To compound these dynamics of resilience, complex systems are nested and cross-scale interactions from smaller and larger scales relative to the system of interest can play formative roles during periods of collapse and reorganization. Large- and small-scale disturbances as well as large-scale system memory/capacity and small-scale innovation can have significant impacts on the trajectory of a reorganizing system (Gunderson and Holling, 2002; Chaffin and Gunderson, 2016). Attempts to measure the property of ecological resilience across complex systems amounts to attempts to measure the persistence of system-controlling variables, including processes, parameters, and important feedbacks, when the system is exposed to varying degrees of disturbance (Folke, 2016).

Experimental study on small group behavior and crowd dynamics in a tall office building evacuation

NASA Astrophysics Data System (ADS)

Ma, Yaping; Li, Lihua; Zhang, Hui; Chen, Tao

2017-05-01

It is well known that a large percentage of occupants in a building are evacuated together with their friends, families, and officemates, especially in China. Small group behaviors are therefore critical for crowd movement. This paper aims to study the crowd dynamic considering different social relations and the impacts of small groups on crowd dynamics in emergency evacuation. Three experiments are conducted in an 11-storey office building. In the first two experiments, all participants are classmates and know each other well. They are evacuated as individuals or pairs. In the third experiment, social relations among the participants are complex. Participants consist of 8 families, 6 lovers and several individuals. Space-time features, speed characteristics and density-speed relations for each experiment are analyzed and compared. Results conclude that small group behaviors can make positive impacts on crowd dynamics when evacuees know each other and are cooperative. This conclusion is also testified by four verified experiments. In the third experiment, speeds of evacuees are lowest. Small groups form automatically with the presence of intimate social relations. Small groups in this experiment slow down the average speed of the crowd and make disturbance on the crowd flow. Small groups in this case make negative impacts on the movement of the crowd. It is because that evacuees do not know each other and they are competitive to each other. Characteristics of different types of small groups are also investigated. Experimental data can provide foundational parameters for evacuation model development and are helpful for building designers.

Socio-ecological dynamics and challenges to the governance of Neglected Tropical Disease control.

PubMed

Michael, Edwin; Madon, Shirin

2017-02-06

The current global attempts to control the so-called "Neglected Tropical Diseases (NTDs)" have the potential to significantly reduce the morbidity suffered by some of the world's poorest communities. However, the governance of these control programmes is driven by a managerial rationality that assumes predictability of proposed interventions, and which thus primarily seeks to improve the cost-effectiveness of implementation by measuring performance in terms of pre-determined outputs. Here, we argue that this approach has reinforced the narrow normal-science model for controlling parasitic diseases, and in doing so fails to address the complex dynamics, uncertainty and socio-ecological context-specificity that invariably underlie parasite transmission. We suggest that a new governance approach is required that draws on a combination of non-equilibrium thinking about the operation of complex, adaptive, systems from the natural sciences and constructivist social science perspectives that view the accumulation of scientific knowledge as contingent on historical interests and norms, if more effective control approaches sufficiently sensitive to local disease contexts are to be devised, applied and managed. At the core of this approach is an emphasis on the need for a process that assists with the inclusion of diverse perspectives, social learning and deliberation, and a reflexive approach to addressing system complexity and incertitude, while balancing this flexibility with stability-focused structures. We derive and discuss a possible governance framework and outline an organizational structure that could be used to effectively deal with the complexity of accomplishing global NTD control. We also point to examples of complexity-based management structures that have been used in parasite control previously, which could serve as practical templates for developing similar governance structures to better manage global NTD control. Our results hold important wider implications for global health policy aiming to effectively control and eradicate parasitic diseases across the world.

Social opinion dynamics is not chaotic

NASA Astrophysics Data System (ADS)

Lim, Chjan; Zhang, Weituo

2016-08-01

Motivated by the research on social opinion dynamics over large and dense networks, a general framework for verifying the monotonicity property of multi-agent dynamics is introduced. This allows a derivation of sociologically meaningful sufficient conditions for monotonicity that are tailor-made for social opinion dynamics, which typically have high nonlinearity. A direct consequence of monotonicity is that social opinion dynamics is nonchaotic. A key part of this framework is the definition of a partial order relation that is suitable for a large class of social opinion dynamics such as the generalized naming games. Comparisons are made to previous techniques to verify monotonicity. Using the results obtained, we extend many of the consequences of monotonicity to this class of social dynamics, including several corollaries on their asymptotic behavior, such as global convergence to consensus and tipping points of a minority fraction of zealots or leaders.

A spread willingness computing-based information dissemination model.

PubMed

Huang, Haojing; Cui, Zhiming; Zhang, Shukui

2014-01-01

This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user's spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network.

A Spread Willingness Computing-Based Information Dissemination Model

PubMed Central

Cui, Zhiming; Zhang, Shukui

2014-01-01

This paper constructs a kind of spread willingness computing based on information dissemination model for social network. The model takes into account the impact of node degree and dissemination mechanism, combined with the complex network theory and dynamics of infectious diseases, and further establishes the dynamical evolution equations. Equations characterize the evolutionary relationship between different types of nodes with time. The spread willingness computing contains three factors which have impact on user's spread behavior: strength of the relationship between the nodes, views identity, and frequency of contact. Simulation results show that different degrees of nodes show the same trend in the network, and even if the degree of node is very small, there is likelihood of a large area of information dissemination. The weaker the relationship between nodes, the higher probability of views selection and the higher the frequency of contact with information so that information spreads rapidly and leads to a wide range of dissemination. As the dissemination probability and immune probability change, the speed of information dissemination is also changing accordingly. The studies meet social networking features and can help to master the behavior of users and understand and analyze characteristics of information dissemination in social network. PMID:25110738

Ponzi scheme diffusion in complex networks

NASA Astrophysics Data System (ADS)

Zhu, Anding; Fu, Peihua; Zhang, Qinghe; Chen, Zhenyue

2017-08-01

Ponzi schemes taking the form of Internet-based financial schemes have been negatively affecting China's economy for the last two years. Because there is currently a lack of modeling research on Ponzi scheme diffusion within social networks yet, we develop a potential-investor-divestor (PID) model to investigate the diffusion dynamics of Ponzi scheme in both homogeneous and inhomogeneous networks. Our simulation study of artificial and real Facebook social networks shows that the structure of investor networks does indeed affect the characteristics of dynamics. Both the average degree of distribution and the power-law degree of distribution will reduce the spreading critical threshold and will speed up the rate of diffusion. A high speed of diffusion is the key to alleviating the interest burden and improving the financial outcomes for the Ponzi scheme operator. The zero-crossing point of fund flux function we introduce proves to be a feasible index for reflecting the fast-worsening situation of fiscal instability and predicting the forthcoming collapse. The faster the scheme diffuses, the higher a peak it will reach and the sooner it will collapse. We should keep a vigilant eye on the harm of Ponzi scheme diffusion through modern social networks.

The dynamics of socio-connective trust within support networks accessed by informal caregivers.

PubMed

Ray, Robin A; Street, Annette F

2011-03-01

This article introduces the concept of socio-connective trust, the synapse between the social structures and processes that underpin relationships in supportive care networks. Data from an ethnographic case study of 18 informal caregivers providing in-home care for people with life-limiting illness were analysed drawing on theoretical concepts from the work of Giddens and writings on social capital, as well as the construction of trust in the caregiving literature. While conceptions of trust were found to contribute to understanding supportive care relationships, they did not account for the dynamic nature of the availability and use of support networks. Instead, informal caregivers undertook ongoing reflexive negotiation of relationship boundaries in response to their own conception of the current situation and their perception of trust in their relationships with the various members of the support network. The concept of socio-connective trust describes the movement and flow of the flexible bonds that influence relationships among care networks and determine the type and range of support accessed by informal caregivers. Understanding the complexities of socio-connective trust in caregiving relationships will assist health and social care workers to mobilize relevant resources to support informal caregivers.

Robustness and Contingent History: From Prisoner's Dilemma to Gaia Theory.

PubMed

Harvey, Inman

2018-01-01

In both social systems and ecosystems there is a need to resolve potential conflicts between the interests of individuals and the collective interest of the community. The collective interests need to survive the turbulent dynamics of social and ecological interactions. To see how different systems with different sets of interactions have different degrees of robustness, we need to look at their different contingent histories. We analyze abstract artificial life models of such systems, and note that some prominent examples rely on explicitly ahistorical frameworks; we point out where analyses that ignore a contingent historical context can be fatally flawed. The mathematical foundations of Gaia theory are presented in a form whose very basic and general assumptions point to wide applicability across complex dynamical systems. This highlights surprising connections between robustness and accumulated contingent happenstance, regardless of whether Darwinian evolution is or is not implicated. Real-life studies highlight the role of history, and artificial life studies should do likewise.

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

Navigability of multiplex temporal network

NASA Astrophysics Data System (ADS)

Wang, Yan; Song, Qiao-Zhen

2017-01-01

Real world complex systems have multiple levels of relationships and in many cases, they need to be modeled as multiplex networks where the same nodes can interact with each other in different layers, such as social networks. However, social relationships only appear at prescribed times so the temporal structures of edge activations can also affect the dynamical processes located above them. To consider both factors are simultaneously, we introduce multiplex temporal networks and propose three different walk strategies to investigate the concurrent dynamics of random walks and the temporal structure of multiplex networks. Thus, we derive analytical results for the multiplex centrality and coverage function in multiplex temporal networks. By comparing them with the numerical results, we show how the underlying topology of the layers and the walk strategy affect the efficiency when exploring the networks. In particular, the most interesting result is the emergence of a super-diffusion process, where the time scale of the multiplex is faster than that of both layers acting separately.

Nonlinear Dynamics, Chaotic and Complex Systems

NASA Astrophysics Data System (ADS)

Infeld, E.; Zelazny, R.; Galkowski, A.

2011-04-01

Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet Speech: Where will the future go? M. J. Feigenbaum.

Intracultural diversity in a model of social dynamics

NASA Astrophysics Data System (ADS)

Parravano, A.; Rivera-Ramirez, H.; Cosenza, M. G.

2007-06-01

We study the consequences of introducing individual nonconformity in social interactions, based on Axelrod's model for the dissemination of culture. A constraint on the number of situations in which interaction may take place is introduced in order to lift the unavoidable homogeneity present in the final configurations arising in Axelrod's related models. The inclusion of this constraint leads to the occurrence of complex patterns of intracultural diversity whose statistical properties and spatial distribution are characterized by means of the concepts of cultural affinity and cultural cline. It is found that the relevant quantity that determines the properties of intracultural diversity is given by the fraction of cultural features that characterizes the cultural nonconformity of individuals.

Rapid adaptation to mammalian sociality via sexually selected traits

PubMed Central

2013-01-01

Background Laboratory studies show that the components of sexual selection (e.g., mate choice and intrasexual competition) can profoundly affect the development and fitness of offspring. Less is known, however, about the total effects of sexual selection on offspring in normal social conditions. Complex social networks, such as dominance hierarchies, regulate the opportunity for mating success, and are often missing from laboratory studies. Social selection is an extended view of sexual selection that incorporates competition during sexual and nonsexual interactions, and predicts complex evolutionary dynamics. Whether social selection improves or constrains offspring fitness is controversial. Results To identify fitness consequences of social selection, wild-derived mice that had bred under laboratory conditions for eight generations were re-introduced to naturalistic competition in enclosures for three consecutive generations (promiscuous line). In parallel, a control lineage bred in cages under random mate assignment (monogamous line). A direct competition experiment using second-generation animals revealed that promiscuous line males had greater reproductive success than monogamous line males (particularly during extra-territorial matings), in spite of higher mortality and equivalent success in social dominance and sperm competition. There were no major female fitness effects (though promiscuous line females had fewer litters than monogamous line females). This result suggested that selection primarily acted upon a sexually attractive male phenotype in the promiscuous line, a hypothesis we confirmed in female odor and mating preference trials. Conclusions We present novel evidence for the strength of sexual selection under normal social conditions, and show rapid male adaptation driven largely by sexual trait expression, with tradeoffs in survivorship and female fecundity. Re-introducing wild-derived mice to competition quickly uncovers sexually selected phenotypes otherwise lost in normal colony breeding. PMID:23577674

Transdisciplinary Application of Cross-Scale Resilience ...

EPA Pesticide Factsheets

The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlyingdiscontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems. Comparative analyses of complex systems have, in fact, demonstrated commonalities among distinctly different types of systems (Schneider & Kay 1994; Holling 2001; Lansing 2003; Foster 2005; Bullmore et al. 2009). Both biological and non-biological complex systems appear t

Executive Functions, Memory, and Social Cognitive Deficits and Recovery in Chronic Alcoholism: A Critical Review to Inform Future Research.

PubMed

Le Berre, Anne-Pascale; Fama, Rosemary; Sullivan, Edith V

2017-08-01

Alcoholism is a complex and dynamic disease, punctuated by periods of abstinence and relapse, and influenced by a multitude of vulnerability factors. Chronic excessive alcohol consumption is associated with cognitive deficits, ranging from mild to severe, in executive functions, memory, and metacognitive abilities, with associated impairment in emotional processes and social cognition. These deficits can compromise efforts in initiating and sustaining abstinence by hampering efficacy of clinical treatment and can obstruct efforts in enabling good decision making success in interpersonal/social interactions, and awareness of cognitive and behavioral dysfunctions. Despite evidence for differences in recovery levels of selective cognitive processes, certain deficits can persist even with prolonged sobriety. Herein is presented a review of alcohol-related cognitive impairments affecting component processes of executive functioning, memory, and the recently investigated cognitive domains of metamemory, social cognition, and emotional processing; also considered are trajectories of cognitive recovery with abstinence. Finally, in the spirit of critical review, limitations of current knowledge are noted and avenues for new research efforts are proposed that focus on (i) the interaction among emotion-cognition processes and identification of vulnerability factors contributing to the development of emotional and social processing deficits and (ii) the time line of cognitive recovery by tracking alcoholism's dynamic course of sobriety and relapse. Knowledge about the heterochronicity of cognitive recovery in alcoholism has the potential of indicating at which points during recovery intervention may be most beneficial. Copyright © 2017 by the Research Society on Alcoholism.

[Medicine at the "edge of chaos". Life, entropy and complexity].

PubMed

De Vito, Eduardo L

2016-01-01

The aim of this paper is to help physicians and health professionals, who constantly seek to improve their knowledge for the benefit of the ill, to incorporate new conceptual and methodological tools to understand the complexity inherent to the field of medicine. This article contains notions that are unfamiliar to these professionals and are intended to foster reflection and learning. It poses the need to define life from a thermodynamic point of view, linking it closely to complex systems, nonlinear dynamics and chaotic behavior, as well as to redefine conventional physiological control mechanisms based on the concept of homeostasis, and to travel the path that starts with the search for extraterrestrial life up to exposing medicine "near the edge of chaos". Complexity transcends the biological aspects; it includes a subjective and symbolic/social dimension. Viewing disease as a heterogeneous and multi-causal phenomenon can give rise to new approaches for the sick.

Accelerating language acquisition.

PubMed

Fowler, W; Ogston, K; Roberts-Fiati, G; Swenson, A

1993-01-01

How much can the development of language and other skills be accelerated in the general population? High correlations between early verbal and mental competencies and parent and teacher language socialization practices suggest enormous potential for widespread improvement. Here we report follow-up research in progress in studies of late adolescent children from diverse ethnic and educational backgrounds who participated in a language enrichment programme during infancy in the home or day-care. In 39 of 44 home-stimulated children located to date (nearly all from college-educated families) 62-93% were: in gifted or advanced programmes, obtaining high grades, avid readers and skilled in writing (over half read before school and wrote creative material independently) and generally highly skilled in verbal, mathematical and other academic domains. They also excelled socially and in sports, and showed intellectual independence. Additional subjects and data (on competence, later experiences and Scholastic Aptitude Test [SAT] scores) are currently being collected. Preliminary data analyses suggest that although early language enrichment can in the short term easily increase competence in all groups well beyond norms generated by current socialization practices, long-term outcomes are a complex function of developmental dynamics between the early, complex, foundation of high skills and motivation for learning, and the interaction with facilitative parental resources.

A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems

NASA Astrophysics Data System (ADS)

Poeppl, Ronald E.; Keesstra, Saskia D.; Maroulis, Jerry

2017-01-01

Human-induced landscape change is difficult to predict due to the complexity inherent in both geomorphic and social systems as well as due to the coupling relationships between them. To better understand system complexity and system response to changing inputs, "connectivity thinking" has become an important recent paradigm within various disciplines including ecology, hydrology and geomorphology. With the presented conceptual connectivity framework on geomorphic change in human-impacted fluvial systems a cautionary note is flagged regarding the need (i) to include and to systematically conceptualise the role of different types of human agency in altering connectivity relationships in geomorphic systems and (ii) to integrate notions of human-environment interactions to connectivity concepts in geomorphology to better explain causes and trajectories of landscape change. Geomorphic response of fluvial systems to human disturbance is shown to be determined by system-specific boundary conditions (incl. system history, related legacy effects and lag times), vegetation dynamics and human-induced functional relationships (i.e. feedback mechanisms) between the different spatial dimensions of connectivity. It is further demonstrated how changes in social systems can trigger a process-response feedback loop between social and geomorphic systems that further governs the trajectory of landscape change in coupled human-geomorphic systems.

Ecological resilience

USGS Publications Warehouse

Allen, Craig R.; Garmestiani, Ahjond S.; Sundstrom, Shana; Angeler, David G.

2016-01-01

Resilience is the capacity of complex systems of people and nature to withstand disturbance without shifting into an alternate regime, or a different type of system organized around different processes and structures (Holling, 1973). Resilience theory was developed to explain the non-linear dynamics of complex adaptive systems, like social-ecological systems (SES) (Walker & Salt, 2006). It is often apparent when the resilience of a SES has been exceeded as the system discernibly changes, such as when a thriving city shifts into a poverty trap, but it is difficult to predict when that shift might occur because of the non-linear dynamics of complex systems. Ecological resilience should not be confused with engineering resilience (Angeler & Allen, 2016), which emphasizes the ability of a SES to perform a specific task consistently and predictably, and to re-establish performance quickly should a disturbance occur. Engineering resilience assumes that complex systems are characterized by a single equilibrium state, and this assumption is not appropriate for complex adaptive systems such as SES. In the risk governance context this means that compounded perturbations derived from hazards or global change can have unexpected and highly uncertain effects on natural resources, humans and societies. These effects can manifest in regime shifts, potentially spurring environmental degradation that might lock SES in an undesirable system state that can be difficult to reverse, and as a consequence economic crises, conflict, human health problems.

Dynamics of analyst forecasts and emergence of complexity: Role of information disparity

PubMed Central

Ahn, Kwangwon

2017-01-01

We report complex phenomena arising among financial analysts, who gather information and generate investment advice, and elucidate them with the help of a theoretical model. Understanding how analysts form their forecasts is important in better understanding the financial market. Carrying out big-data analysis of the analyst forecast data from I/B/E/S for nearly thirty years, we find skew distributions as evidence for emergence of complexity, and show how information asymmetry or disparity affects financial analysts’ forming their forecasts. Here regulations, information dissemination throughout a fiscal year, and interactions among financial analysts are regarded as the proxy for a lower level of information disparity. It is found that financial analysts with better access to information display contrasting behaviors: a few analysts become bolder and issue forecasts independent of other forecasts while the majority of analysts issue more accurate forecasts and flock to each other. Main body of our sample of optimistic forecasts fits a log-normal distribution, with the tail displaying a power law. Based on the Yule process, we propose a model for the dynamics of issuing forecasts, incorporating interactions between analysts. Explaining nicely empirical data on analyst forecasts, this provides an appealing instance of understanding social phenomena in the perspective of complex systems. PMID:28498831

Coevolving complex networks in the model of social interactions

NASA Astrophysics Data System (ADS)

Raducha, Tomasz; Gubiec, Tomasz

2017-04-01

We analyze Axelrod's model of social interactions on coevolving complex networks. We introduce four extensions with different mechanisms of edge rewiring. The models are intended to catch two kinds of interactions-preferential attachment, which can be observed in scientists or actors collaborations, and local rewiring, which can be observed in friendship formation in everyday relations. Numerical simulations show that proposed dynamics can lead to the power-law distribution of nodes' degree and high value of the clustering coefficient, while still retaining the small-world effect in three models. All models are characterized by two phase transitions of a different nature. In case of local rewiring we obtain order-disorder discontinuous phase transition even in the thermodynamic limit, while in case of long-distance switching discontinuity disappears in the thermodynamic limit, leaving one continuous phase transition. In addition, we discover a new and universal characteristic of the second transition point-an abrupt increase of the clustering coefficient, due to formation of many small complete subgraphs inside the network.

Socio-Technical Perspective on Interdisciplinary Interactions During the Development of Complex Engineered Systems

NASA Technical Reports Server (NTRS)

McGowan, Anna-Maria R.; Daly, Shanna; Baker, Wayne; Papalambros, panos; Seifert, Colleen

2013-01-01

This study investigates interdisciplinary interactions that take place during the research, development, and early conceptual design phases in the design of large-scale complex engineered systems (LaCES) such as aerospace vehicles. These interactions, that take place throughout a large engineering development organization, become the initial conditions of the systems engineering process that ultimately leads to the development of a viable system. This paper summarizes some of the challenges and opportunities regarding social and organizational issues that emerged from a qualitative study using ethnographic and survey data. The analysis reveals several socio-technical couplings between the engineered system and the organization that creates it. Survey respondents noted the importance of interdisciplinary interactions and their benefits to the engineered system as well as substantial challenges in interdisciplinary interactions. Noted benefits included enhanced knowledge and problem mitigation and noted obstacles centered on organizational and human dynamics. Findings suggest that addressing the social challenges may be a critical need in enabling interdisciplinary interactions

The politics of biofuels, land and agrarian change: editors' introduction.

PubMed

Borras, Saturnino M

2010-01-01

This introduction frames key questions on biofuels, land and agrarian change within agrarian political economy, political sociology and political ecology. It identifies and explains big questions that provide the starting point for the contributions to this collection. We lay out some of the emerging themes which define the politics of biofuels, land and agrarian change revolving around global (re)configurations; agro-ecological visions; conflicts, resistances and diverse outcomes; state, capital and society relations; mobilising opposition, creating alternatives; and change and continuity. An engaged agrarian political economy combined with global political economy, international relations and social movement theory provides an important framework for analysis and critique of the conditions, dynamics, contradictions, impacts and possibilities of the emerging global biofuels complex. Our hope is that this collection demonstrates the significance of a political economy of biofuels in capturing the complexity of the "biofuels revolution" and at the same time opening up questions about its sustainability in social and environmental terms that provide pathways towards alternatives.

Where you stand depends on where you sit: Qualitative inquiry into notions of fire adaptation

Treesearch

Hannah Brenkert-Smith; James R. Meldrum; Patricia A. Champ; Christopher M. Barth

2017-01-01

Wildfire and the threat it poses to society represents an example of the complex, dynamic relationship between social and ecological systems. Increasingly, wildfire adaptation is posited as a pathway to shift the approach to fire from a suppression paradigm that seeks to control fire to a paradigm that focuses on “living with” and “adapting to” wildfire. In this study...

A Systems-Based Conceptual Framework for Assessing the Determinants of a Social License to Operate in the Mining Industry

NASA Astrophysics Data System (ADS)

Prno, Jason; Slocombe, D. Scott

2014-03-01

The concept of a "social license to operate" (SLO) was coined in the 1990s and gained popularity as one way in which "social" considerations can be addressed in mineral development decision making. The need for a SLO implies that developers require the widespread approval of local community members for their projects to avoid exposure to potentially costly conflict and business risks. Only a limited amount of scholarship exists on the topic, and there is a need for research that specifically addresses the complex and changeable nature of SLO outcomes. In response to these challenges, this paper advances a novel, systems-based conceptual framework for assessing SLO determinants and outcomes in the mining industry. Two strands of systems theory are specifically highlighted—complex adaptive systems and resilience—and the roles of context, key system variables, emergence, change, uncertainty, feedbacks, cross-scale effects, multiple stable states, thresholds, and resilience are discussed. The framework was developed from the results of a multi-year research project which involved international mining case study investigations, a comprehensive literature review, and interviews conducted with mining stakeholders and observers. The framework can help guide SLO analysis and management efforts, by encouraging users to account for important contextual and complexity-oriented elements present in SLO settings. We apply the framework to a case study in Alaska, USA before discussing its merits and challenges. We also illustrate knowledge gaps associated with applications of complex adaptive systems and resilience theories to the study of SLO dynamics, and discuss opportunities for future research.

A systems-based conceptual framework for assessing the determinants of a social license to operate in the mining industry.

PubMed

Prno, Jason; Slocombe, D Scott

2014-03-01

The concept of a "social license to operate" (SLO) was coined in the 1990s and gained popularity as one way in which "social" considerations can be addressed in mineral development decision making. The need for a SLO implies that developers require the widespread approval of local community members for their projects to avoid exposure to potentially costly conflict and business risks. Only a limited amount of scholarship exists on the topic, and there is a need for research that specifically addresses the complex and changeable nature of SLO outcomes. In response to these challenges, this paper advances a novel, systems-based conceptual framework for assessing SLO determinants and outcomes in the mining industry. Two strands of systems theory are specifically highlighted-complex adaptive systems and resilience-and the roles of context, key system variables, emergence, change, uncertainty, feedbacks, cross-scale effects, multiple stable states, thresholds, and resilience are discussed. The framework was developed from the results of a multi-year research project which involved international mining case study investigations, a comprehensive literature review, and interviews conducted with mining stakeholders and observers. The framework can help guide SLO analysis and management efforts, by encouraging users to account for important contextual and complexity-oriented elements present in SLO settings. We apply the framework to a case study in Alaska, USA before discussing its merits and challenges. We also illustrate knowledge gaps associated with applications of complex adaptive systems and resilience theories to the study of SLO dynamics, and discuss opportunities for future research.

Is the person-situation debate important for agent-based modeling and vice-versa?

PubMed

Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał

2014-01-01

Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not. Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature. This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

Social cohesion through football: a quasi-experimental mixed methods design to evaluate a complex health promotion program

PubMed Central

2010-01-01

Social isolation and disengagement fragments local communities. Evidence indicates that refugee families are highly vulnerable to social isolation in their countries of resettlement. Research to identify approaches to best address this is needed. Football United is a program that aims to foster social inclusion and cohesion in areas with high refugee settlement in New South Wales, Australia, through skills and leadership development, mentoring, and the creation of links with local community and corporate leaders and organisations. The Social Cohesion through Football study's broad goal is to examine the implementation of a complex health promotion program, and to analyse the processes involved in program implementation. The study will consider program impact on individual health and wellbeing, social inclusion and cohesion, as well as analyse how the program by necessity interacts and adapts to context during implementation, a concept we refer to as plasticity. The proposed study will be the first prospective cohort impact study to our knowledge to assess the impact of a comprehensive integrated program using football as a vehicle for fostering social inclusion and cohesion in communities with high refugee settlement. Methods/design A quasi-experimental cohort study design with treatment partitioning involving four study sites. The study employs a 'dose response' model, comparing those with no involvement in the Football United program with those with lower or higher levels of participation. A range of qualitative and quantitative measures will be used in the study. Study participants' emotional well being, resilience, ethnic identity and other group orientation, feelings of social inclusion and belonging will be measured using a survey instrument complemented by relevant data drawn from in-depth interviews, self reporting measures and participant observation. The views of key informants from the program and the wider community will also be solicited. Discussion The complexity of the Football United program poses challenges for measurement, and requires the study design to be responsive to the dynamic nature of the program and context. Assessment of change is needed at multiple levels, drawing on mixed methods and multidisciplinary approaches in implementation and evaluation. Attention to these challenges has underpinned the design and methods in the Social Cohesion through Football study, which will use a unique and innovative combination of measures that have not been applied together previously in social inclusion/cohesion and sport and social inclusion/cohesion program research. PMID:20920361

Social cohesion through football: a quasi-experimental mixed methods design to evaluate a complex health promotion program.

PubMed

Nathan, Sally; Bunde-Birouste, Anne; Evers, Clifton; Kemp, Lynn; MacKenzie, Julie; Henley, Robert

2010-10-05

Social isolation and disengagement fragments local communities. Evidence indicates that refugee families are highly vulnerable to social isolation in their countries of resettlement. Research to identify approaches to best address this is needed. Football United is a program that aims to foster social inclusion and cohesion in areas with high refugee settlement in New South Wales, Australia, through skills and leadership development, mentoring, and the creation of links with local community and corporate leaders and organisations. The Social Cohesion through Football study's broad goal is to examine the implementation of a complex health promotion program, and to analyse the processes involved in program implementation. The study will consider program impact on individual health and wellbeing, social inclusion and cohesion, as well as analyse how the program by necessity interacts and adapts to context during implementation, a concept we refer to as plasticity. The proposed study will be the first prospective cohort impact study to our knowledge to assess the impact of a comprehensive integrated program using football as a vehicle for fostering social inclusion and cohesion in communities with high refugee settlement. A quasi-experimental cohort study design with treatment partitioning involving four study sites. The study employs a 'dose response' model, comparing those with no involvement in the Football United program with those with lower or higher levels of participation. A range of qualitative and quantitative measures will be used in the study. Study participants' emotional well being, resilience, ethnic identity and other group orientation, feelings of social inclusion and belonging will be measured using a survey instrument complemented by relevant data drawn from in-depth interviews, self reporting measures and participant observation. The views of key informants from the program and the wider community will also be solicited. The complexity of the Football United program poses challenges for measurement, and requires the study design to be responsive to the dynamic nature of the program and context. Assessment of change is needed at multiple levels, drawing on mixed methods and multidisciplinary approaches in implementation and evaluation. Attention to these challenges has underpinned the design and methods in the Social Cohesion through Football study, which will use a unique and innovative combination of measures that have not been applied together previously in social inclusion/cohesion and sport and social inclusion/cohesion program research.

The role of social engagement and identity in community mobility among older adults aging in place.

PubMed

Gardner, Paula

2014-01-01

The purpose of this study was to understand how neighbourhoods - as physical and social environments - influence community mobility. Seeking an insider's perspective, the study employed an ethnographic research design. Immersed within the daily lives of 6 older adults over an 8-month period, auditory, textual, and visual data was collected using the "go-along" interview method. During these interviews, the researcher accompanied participants on their natural outings while actively exploring their physical and social practices by asking questions, listening, and observing. Findings highlight a process of community mobility that is complex, dynamic and often difficult as participant's ability and willingness to journey into their neighborhoods were challenged by a myriad of individual and environmental factors that changed from one day to the next. Concerned in particular with the social environment, final analysis reveals how key social factors - social engagement and identity - play a critical role in the community mobility of older adults aging in place. Identity and social engagement are important social factors that play a role in community mobility. The need for social engagement and the preservation of identity are such strong motivators for community mobility that they can "trump" poor health, pain, functional ability and hazardous conditions. To effectively promote community mobility, the social lives and needs of individuals must be addressed.

Temporal and spatial changes in social vulnerability to natural hazards

PubMed Central

Cutter, Susan L.; Finch, Christina

2008-01-01

During the past four decades (1960–2000), the United States experienced major transformations in population size, development patterns, economic conditions, and social characteristics. These social, economic, and built-environment changes altered the American hazardscape in profound ways, with more people living in high-hazard areas than ever before. To improve emergency management, it is important to recognize the variability in the vulnerable populations exposed to hazards and to develop place-based emergency plans accordingly. The concept of social vulnerability identifies sensitive populations that may be less likely to respond to, cope with, and recover from a natural disaster. Social vulnerability is complex and dynamic, changing over space and through time. This paper presents empirical evidence on the spatial and temporal patterns in social vulnerability in the United States from 1960 to the present. Using counties as our study unit, we found that those components that consistently increased social vulnerability for all time periods were density (urban), race/ethnicity, and socioeconomic status. The spatial patterning of social vulnerability, although initially concentrated in certain geographic regions, has become more dispersed over time. The national trend shows a steady reduction in social vulnerability, but there is considerable regional variability, with many counties increasing in social vulnerability during the past five decades. PMID:18268336

Intergroup Variation of Social Relationships in Wild Vervet Monkeys: A Dynamic Network Approach.

PubMed

Borgeaud, Christèle; Sosa, Sebastian; Bshary, Redouan; Sueur, Cédric; van de Waal, Erica

2016-01-01

Social network analysis is a powerful tool that enables us to describe and quantify relationships between individuals. So far most of the studies rely on the analyses of various network snapshots, but do not capture changes over time. Here we use a stochastic actor-oriented model (SAOM) to test both the structure and the dynamics of relationships of three groups of wild vervet monkeys. We found that triadic closure (i.e., the friend of a friend is a friend) was significant in all three groups while degree popularity (i.e., the willingness to associate with individuals with high degree of connections) was significant in only two groups (AK, BD). The structure and dynamics of relationships according to the attributes of sex, matrilineand age differed significantly among groups. With respect to the structure, when analyzing the likelihood of bonds according to the different attributes, we found that individuals associate themselves preferably to individuals of the same sex only in two groups (AK, NH), while significant results for attachment to individuals of the same matriline were found also in two groups (BD, NH). With respect to the dynamics, i.e., how quickly relationships are modified, we found in two groups (AK, BD) that females' relationships were more prone to variation than males.' In the BD group, relationships within high-ranking matrilines were less stable than low-ranking ones while in the NH group, juveniles' relationships were also less stable than adults' ones. The intergroup variation indicates that establishing species-specific or even population specific characteristics of social networks for later between-species comparisons will be challenging. Although, such variation could also indicate some methodological issue, we are quite confident that data was collected similarly within the different groups. Our study therefore provides a potential new method to quantify social complexity according to natural demographic variation.

Operationalizing safe operating space for regional social-ecological systems.

PubMed

Hossain, Md Sarwar; Dearing, John A; Eigenbrod, Felix; Johnson, Fiifi Amoako

2017-04-15

This study makes a first attempt to operationalize the safe operating space concept at a regional scale by considering the complex dynamics (e.g. non-linearity, feedbacks, and interactions) within a systems dynamic model (SD). We employ the model to explore eight 'what if' scenarios based on well-known challenges (e.g. climate change) and current policy debates (e.g. subsidy withdrawal). The findings show that the social-ecological system in the Bangladesh delta may move beyond a safe operating space when a withdrawal of a 50% subsidy for agriculture is combined with the effects of a 2°C temperature increase and sea level rise. Further reductions in upstream river discharge in the Ganges would push the system towards a dangerous zone once a 3.5°C temperature increase was reached. The social-ecological system in Bangladesh delta may be operated within a safe space by: 1) managing feedback (e.g. by reducing production costs) and the slow biophysical variables (e.g. temperature, rainfall) to increase the long-term resilience, 2) negotiating for transboundary water resources, and 3) revising global policies (e.g. withdrawal of subsidy) that negatively impact at regional scales. This study demonstrates how the concepts of tipping points, limits to adaptations, and boundaries for sustainable development may be defined in real world social-ecological systems. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Detection of communities with Naming Game-based methods

PubMed Central

Ribeiro, Carlos Henrique Costa

2017-01-01

Complex networks are often organized in groups or communities of agents that share the same features and/or functions, and this structural organization is built naturally with the formation of the system. In social networks, we argue that the dynamic of linguistic interactions of agreement among people can be a crucial factor in generating this community structure, given that sharing opinions with another person bounds them together, and disagreeing constantly would probably weaken the relationship. We present here a computational model of opinion exchange that uncovers the community structure of a network. Our aim is not to present a new community detection method proper, but to show how a model of social communication dynamics can reveal the (simple and overlapping) community structure in an emergent way. Our model is based on a standard Naming Game, but takes into consideration three social features: trust, uncertainty and opinion preference, that are built over time as agents communicate among themselves. We show that the separate addition of each social feature in the Naming Game results in gradual improvements with respect to community detection. In addition, the resulting uncertainty and trust values classify nodes and edges according to role and position in the network. Also, our model has shown a degree of accuracy both for non-overlapping and overlapping communities that are comparable with most algorithms specifically designed for topological community detection. PMID:28797097

Social complexity as a proximate and ultimate factor in communicative complexity

PubMed Central

Freeberg, Todd M.; Dunbar, Robin I. M.; Ord, Terry J.

2012-01-01

The ‘social complexity hypothesis’ for communication posits that groups with complex social systems require more complex communicative systems to regulate interactions and relations among group members. Complex social systems, compared with simple social systems, are those in which individuals frequently interact in many different contexts with many different individuals, and often repeatedly interact with many of the same individuals in networks over time. Complex communicative systems, compared with simple communicative systems, are those that contain a large number of structurally and functionally distinct elements or possess a high amount of bits of information. Here, we describe some of the historical arguments that led to the social complexity hypothesis, and review evidence in support of the hypothesis. We discuss social complexity as a driver of communication and possible causal factor in human language origins. Finally, we discuss some of the key current limitations to the social complexity hypothesis—the lack of tests against alternative hypotheses for communicative complexity and evidence corroborating the hypothesis from modalities other than the vocal signalling channel. PMID:22641818

A Novel Interdisciplinary Approach to Socio-Technical Complexity

NASA Astrophysics Data System (ADS)

Bassetti, Chiara

The chapter presents a novel interdisciplinary approach that integrates micro-sociological analysis into computer-vision and pattern-recognition modeling and algorithms, the purpose being to tackle socio-technical complexity at a systemic yet micro-grounded level. The approach is empirically-grounded and both theoretically- and analytically-driven, yet systemic and multidimensional, semi-supervised and computable, and oriented towards large scale applications. The chapter describes the proposed approach especially as for its sociological foundations, and as applied to the analysis of a particular setting --i.e. sport-spectator crowds. Crowds, better defined as large gatherings, are almost ever-present in our societies, and capturing their dynamics is crucial. From social sciences to public safety management and emergency response, modeling and predicting large gatherings' presence and dynamics, thus possibly preventing critical situations and being able to properly react to them, is fundamental. This is where semi/automated technologies can make the difference. The work presented in this chapter is intended as a scientific step towards such an objective.

Fast social-like learning of complex behaviors based on motor motifs.

PubMed

Calvo Tapia, Carlos; Tyukin, Ivan Y; Makarov, Valeri A

2018-05-01

Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a complex behavior can be decomposed into a sequence of n motor motifs. Then a neural network capable of activating motor motifs in a given sequence can drive an agent. To account for (n-1)! possible sequences of motifs in a neural network, we employ the winnerless competition approach. We then consider a teacher-learner situation: one agent exhibits a complex movement, while another one aims at mimicking the teacher's behavior. Despite the huge variety of possible motif sequences we show that the learner, equipped with the provided learning model, can rewire "on the fly" its synaptic couplings in no more than (n-1) learning cycles and converge exponentially to the durations of the teacher's motifs. We validate the learning model on mobile robots. Experimental results show that the learner is indeed capable of copying the teacher's behavior composed of six motor motifs in a few learning cycles. The reported mechanism of learning is general and can be used for replicating different functions, including, for example, sound patterns or speech.

Fast social-like learning of complex behaviors based on motor motifs

NASA Astrophysics Data System (ADS)

Calvo Tapia, Carlos; Tyukin, Ivan Y.; Makarov, Valeri A.

2018-05-01

Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a complex behavior can be decomposed into a sequence of n motor motifs. Then a neural network capable of activating motor motifs in a given sequence can drive an agent. To account for (n -1 )! possible sequences of motifs in a neural network, we employ the winnerless competition approach. We then consider a teacher-learner situation: one agent exhibits a complex movement, while another one aims at mimicking the teacher's behavior. Despite the huge variety of possible motif sequences we show that the learner, equipped with the provided learning model, can rewire "on the fly" its synaptic couplings in no more than (n -1 ) learning cycles and converge exponentially to the durations of the teacher's motifs. We validate the learning model on mobile robots. Experimental results show that the learner is indeed capable of copying the teacher's behavior composed of six motor motifs in a few learning cycles. The reported mechanism of learning is general and can be used for replicating different functions, including, for example, sound patterns or speech.

Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

The Evolution of Cooperation in Managed Groundwater Systems: An Agent-Based Modelling Approach

NASA Astrophysics Data System (ADS)

Castilla Rho, J. C.; Mariethoz, G.; Rojas, R. F.; Andersen, M. S.; Kelly, B. F.; Holley, C.

2014-12-01

Human interactions with groundwater systems often exhibit complex features that hinder the sustainable management of the resource. This leads to costly and persistent conflicts over groundwater at the catchment scale. One possible way to address these conflicts is by gaining a better understanding of how social and groundwater dynamics coevolve using agent-based models (ABM). Such models allow exploring 'bottom-up' solutions (i.e., self-organised governance systems), where the behaviour of individual agents (e.g., farmers) results in the emergence of mutual cooperation among groundwater users. There is significant empirical evidence indicating that this kind of 'bottom-up' approach may lead to more enduring and sustainable outcomes, compared to conventional 'top-down' strategies such as centralized control and water right schemes (Ostrom 1990). New modelling tools are needed to study these concepts systematically and efficiently. Our model uses a conceptual framework to study cooperation and the emergence of social norms as initially proposed by Axelrod (1986), which we adapted to groundwater management. We developed an ABM that integrates social mechanisms and the physics of subsurface flow. The model explicitly represents feedback between groundwater conditions and social dynamics, capturing the spatial structure of these interactions and the potential effects on cooperation levels in an agricultural setting. Using this model, we investigate a series of mechanisms that may trigger norms supporting cooperative strategies, which can be sustained and become stable over time. For example, farmers in a self-monitoring community can be more efficient at achieving the objective of sustainable groundwater use than government-imposed regulation. Our coupled model thus offers a platform for testing new schemes promoting cooperation and improved resource use, which can be used as a basis for policy design. Importantly, we hope to raise awareness of agent-based modelling as a new tool for studying complex human-groundwater systems.

Marine reserves as linked social-ecological systems.

PubMed

Pollnac, Richard; Christie, Patrick; Cinner, Joshua E; Dalton, Tracey; Daw, Tim M; Forrester, Graham E; Graham, Nicholas A J; McClanahan, Timothy R

2010-10-26

Marine reserves are increasingly recognized as having linked social and ecological dynamics. This study investigates how the ecological performance of 56 marine reserves throughout the Philippines, Caribbean, and Western Indian Ocean (WIO) is related to both reserve design features and the socioeconomic characteristics in associated coastal communities. Ecological performance was measured as fish biomass in the reserve relative to nearby areas. Of the socioeconomic variables considered, human population density and compliance with reserve rules had the strongest effects on fish biomass, but the effects of these variables were region specific. Relationships between population density and the reserve effect on fish biomass were negative in the Caribbean, positive in the WIO, and not detectable in the Philippines. Differing associations between population density and reserve effectiveness defy simple explanation but may depend on human migration to effective reserves, depletion of fish stocks outside reserves, or other social factors that change with population density. Higher levels of compliance reported by resource users was related to higher fish biomass in reserves compared with outside, but this relationship was only statistically significant in the Caribbean. A heuristic model based on correlations between social, cultural, political, economic, and other contextual conditions in 127 marine reserves showed that high levels of compliance with reserve rules were related to complex social interactions rather than simply to enforcement of reserve rules. Comparative research of this type is important for uncovering the complexities surrounding human dimensions of marine reserves and improving reserve management.

Prediction of missing links and reconstruction of complex networks

NASA Astrophysics Data System (ADS)

Zhang, Cheng-Jun; Zeng, An

2016-04-01

Predicting missing links in complex networks is of great significance from both theoretical and practical point of view, which not only helps us understand the evolution of real systems but also relates to many applications in social, biological and online systems. In this paper, we study the features of different simple link prediction methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Moreover, we find that high prediction accuracy is not definitely corresponding to a high performance in preserving the network properties when using link prediction methods to reconstruct networks. Our work highlights the importance of considering the feedback effect of the link prediction methods on network properties when designing the algorithms.

Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties

PubMed Central

Eom, Young-Ho; Puliga, Michelangelo; Smailović, Jasmina; Mozetič, Igor; Caldarelli, Guido

2015-01-01

Large-scale data from social media have a significant potential to describe complex phenomena in the real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the election outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media. PMID:26161795

Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties.

PubMed

Eom, Young-Ho; Puliga, Michelangelo; Smailović, Jasmina; Mozetič, Igor; Caldarelli, Guido

2015-01-01

Large-scale data from social media have a significant potential to describe complex phenomena in the real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the election outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.

Sex-specific mechanism of social hierarchy in mice.

PubMed

van den Berg, Wouter E; Lamballais, Sander; Kushner, Steven A

2015-05-01

The establishment of social hierarchies is a naturally occurring, evolutionarily conserved phenomenon with a well-established impact on fitness and health. Investigations of complex social group dynamics may offer novel opportunities for translational studies of autism spectrum disorder. Here we describe a robust behavioral paradigm using an automated version of the tube test. Isogenic groups of male and female mice establish linear social hierarchies that remain highly stable for at least 14 days, the longest interval tested. Remarkably, however, their social strategy is sex-specific: females primarily utilize intrinsic attributes, whereas males are strongly influenced by prior social experience. Using both genetic and pharmacological manipulations, we identify testosterone as a critical sex-specific factor for determining which social strategy is used. Males inheriting a null mutation of the sex-determining region Y (Sry) gene used a similar social cognitive strategy as females. In contrast, females with transgenic expression of Sry utilized a typically male social strategy. Analogously, castration of males and testosterone supplementation of females yielded similar outcomes, with a reversal of their social cognitive strategy. Together, our results demonstrate a sex-specific mechanism underlying social hierarchy, in which both males and females retain the functional capacity to adapt their social strategy. More generally, we expect the automated tube test to provide an important complementary approach for both fundamental and translational studies of social behavior.

When complexity science meets implementation science: a theoretical and empirical analysis of systems change.

PubMed

Braithwaite, Jeffrey; Churruca, Kate; Long, Janet C; Ellis, Louise A; Herkes, Jessica

2018-04-30

Implementation science has a core aim - to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents of complexity science research and the conception of complexity feature to reveal the complexity features of LUCC research in urbanization process. Urban space system is a complex economic and cultural phenomenon as well as a social process, is the comprehensive characterization of urban society, economy and culture, and is a complex space system formed by society, economy and nature. It has dissipative structure characteristics, such as opening, dynamics, self-organization, non-balance etc. Traditional model cannot simulate these social, economic and natural driving forces of LUCC including main feedback relation from LUCC to driving force. 2. Establishment of Markov extended model of LUCC analog research in urbanization process. Firstly, use traditional LUCC research model to compute change speed of regional land use through calculating dynamic degree, exploitation degree and consumption degree of land use; use the theory of fuzzy set to rewrite the traditional Markov model, establish structure transfer matrix of land use, forecast and analyze dynamic change and development trend of land use, and present noticeable problems and corresponding measures in urbanization process according to research results. 3. Application of intelligent computation research and complexity science research method in LUCC analog model in urbanization process. On the basis of detailed elaboration of the theory and the model of LUCC research in urbanization process, analyze the problems of existing model used in LUCC research (namely, difficult to resolve many complexity phenomena in complex urban space system), discuss possible structure realization forms of LUCC analog research in combination with the theories of intelligent computation and complexity science research. Perform application analysis on BP artificial neural network and genetic algorithms of intelligent computation and CA model and MAS technology of complexity science research, discuss their theoretical origins and their own characteristics in detail, elaborate the feasibility of them in LUCC analog research, and bring forward improvement methods and measures on existing problems of this kind of model. 4. Establishment of LUCC analog model in urbanization process based on theories of intelligent computation and complexity science. Based on the research on abovementioned BP artificial neural network, genetic algorithms, CA model and multi-agent technology, put forward improvement methods and application assumption towards their expansion on geography, build LUCC analog model in urbanization process based on CA model and Agent model, realize the combination of learning mechanism of BP artificial neural network and fuzzy logic reasoning, express the regulation with explicit formula, and amend the initial regulation through self study; optimize network structure of LUCC analog model and methods and procedures of model parameters with genetic algorithms. In this paper, I introduce research theory and methods of complexity science into LUCC analog research and presents LUCC analog model based upon CA model and MAS theory. Meanwhile, I carry out corresponding expansion on traditional Markov model and introduce the theory of fuzzy set into data screening and parameter amendment of improved model to improve the accuracy and feasibility of Markov model in the research on land use/cover change.

Conceptualising population health: from mechanistic thinking to complexity science.

PubMed

Jayasinghe, Saroj

2011-01-20

The mechanistic interpretation of reality can be traced to the influential work by René Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections.

Low-level visual attention and its relation to joint attention in autism spectrum disorder.

PubMed

Jaworski, Jessica L Bean; Eigsti, Inge-Marie

2017-04-01

Visual attention is integral to social interaction and is a critical building block for development in other domains (e.g., language). Furthermore, atypical attention (especially joint attention) is one of the earliest markers of autism spectrum disorder (ASD). The current study assesses low-level visual attention and its relation to social attentional processing in youth with ASD and typically developing (TD) youth, aged 7 to 18 years. The findings indicate difficulty overriding incorrect attentional cues in ASD, particularly with non-social (arrow) cues relative to social (face) cues. The findings also show reduced competition in ASD from cues that remain on-screen. Furthermore, social attention, autism severity, and age were all predictors of competing cue processing. The results suggest that individuals with ASD may be biased towards speeded rather than accurate responding, and further, that reduced engagement with visual information may impede responses to visual attentional cues. Once attention is engaged, individuals with ASD appear to interpret directional cues as meaningful. These findings from a controlled, experimental paradigm were mirrored in results from an ecologically valid measure of social attention. Attentional difficulties may be exacerbated during the complex and dynamic experience of actual social interaction. Implications for intervention are discussed.

[Youths in the shantytowns (favelas) of Rio de Janeiro/Brazil: from social vulnerability to opportunities for human development].

PubMed

Figueiredo, Gustavo de Oliveira

2016-08-01

Based on a review of living conditions in the complex and dynamic reality of the shantytowns ("favelas") of Rio de Janeiro and the main difficulties facing the human development of youths in this context, we analyze the social protection function involved in educational projects that offer new opportunities for life. In this article we analyze the relationship between the variables of social exclusion, poverty and violence, jointly grouped in the social vulnerability category, and the variables related to opportunities for human development grouped in the resilience category. The socio-educational projects constitute an important factor of resilience, able to influence the subjective development of young people and impact the improvement in the quality of life in the favelas. The social recognition and the relationship of trust established with educators and other youths in similar situations foster efforts to develop changes in attitude and to build new possibilities of life in spite of social vulnerability. The opportunity to experience interpersonal relationships, emotional bonds and positive social interaction can promote changes in the world view of youths and elicit a desire to change their living conditions and enhance their projects for the future.

Power-law Growth and Punctuated Equilibrium Dynamics in Water Resources Systems

NASA Astrophysics Data System (ADS)

Parolari, A.; Katul, G. G.; Porporato, A. M.

2015-12-01

The global rise in population-driven water scarcity and recent appreciation of strong dynamic coupling between human and natural systems has called for new approaches to predict the future sustainability of regional and global water resources systems. The dynamics of coupled human-water systems are driven by a complex set of social, environmental, and technological factors. Present projections of water resources systems range from a finite carrying capacity regulated by accessible freshwater, or `peak renewable water,' to punctuated evolution with new supplied and improved efficiency gained from technological and social innovation. However, these projections have yet to be quantified from observations or in a comprehensive theoretical framework. Using data on global water withdrawals and storage capacity of regional water supply systems, non-trivial dynamics are identified in water resources systems development over time, including power-law growth and punctuated equilibria. Two models are introduced to explain this behavior: (1) a delay differential equation and (2) a power-law with log-periodic oscillations, both of which rely on past conditions (or system memory) to describe the present rate of growth in the system. In addition, extension of the first model demonstrates how system delays and punctuated equilibria can emerge from coupling between human population growth and associated resource demands. Lastly, anecdotal evidence is used to demonstrate the likelihood of power-law growth in global water use from the agricultural revolution 3000 BC to the present. In a practical sense, the presence of these patterns in models with delayed oscillations suggests that current decision-making related to water resources development results from the historical accumulation of resource use decisions, technological and social changes, and their consequences.

Building a Community of Research Practice: Intragroup Team Social Dynamics in Interdisciplinary Mixed Methods

ERIC Educational Resources Information Center

Hemmings, Annette; Beckett, Gulbahar; Kennerly, Susan; Yap, Tracey

2013-01-01

This article explicates the intragroup social dynamics and work of a nursing and education research team as a community of research practice interested in organizational cultures and occupational subcultures. Dynamics were characterized by processes of socialization through reeducation and group social identity formation that enabled members to…

Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

ClueNet: Clustering a temporal network based on topological similarity rather than denseness.

PubMed

Crawford, Joseph; Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.

Dynamic neural architecture for social knowledge retrieval

PubMed Central

Wang, Yin; Collins, Jessica A.; Koski, Jessica; Nugiel, Tehila; Metoki, Athanasia; Olson, Ingrid R.

2017-01-01

Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. In our daily life, we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often guide our decisions as we navigate complex social interactions. Even abstract traits associated with an individual, such as their political affiliation, can cue a rich cascade of person-specific knowledge. Here, we asked whether the anterior temporal lobe (ATL) serves as a hub for a distributed neural circuit that represents person knowledge. Fifty participants across two studies learned biographical information about fictitious people in a 2-d training paradigm. On day 3, they retrieved this biographical information while undergoing an fMRI scan. A series of multivariate and connectivity analyses suggest that the ATL stores abstract person identity representations. Moreover, this region coordinates interactions with a distributed network to support the flexible retrieval of person attributes. Together, our results suggest that the ATL is a central hub for representing and retrieving person knowledge. PMID:28289200

The coevolution of recognition and social behavior.

PubMed

Smead, Rory; Forber, Patrick

2016-05-26

Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation.

The coevolution of recognition and social behavior

PubMed Central

Smead, Rory; Forber, Patrick

2016-01-01

Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation. PMID:27225673

Dynamic neural architecture for social knowledge retrieval.

PubMed

Wang, Yin; Collins, Jessica A; Koski, Jessica; Nugiel, Tehila; Metoki, Athanasia; Olson, Ingrid R

2017-04-18

Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. In our daily life, we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often guide our decisions as we navigate complex social interactions. Even abstract traits associated with an individual, such as their political affiliation, can cue a rich cascade of person-specific knowledge. Here, we asked whether the anterior temporal lobe (ATL) serves as a hub for a distributed neural circuit that represents person knowledge. Fifty participants across two studies learned biographical information about fictitious people in a 2-d training paradigm. On day 3, they retrieved this biographical information while undergoing an fMRI scan. A series of multivariate and connectivity analyses suggest that the ATL stores abstract person identity representations. Moreover, this region coordinates interactions with a distributed network to support the flexible retrieval of person attributes. Together, our results suggest that the ATL is a central hub for representing and retrieving person knowledge.

Causal learning is collaborative: Examining explanation and exploration in social contexts.

PubMed

Legare, Cristine H; Sobel, David M; Callanan, Maureen

2017-10-01

Causal learning in childhood is a dynamic and collaborative process of explanation and exploration within complex physical and social environments. Understanding how children learn causal knowledge requires examining how they update beliefs about the world given novel information and studying the processes by which children learn in collaboration with caregivers, educators, and peers. The objective of this article is to review evidence for how children learn causal knowledge by explaining and exploring in collaboration with others. We review three examples of causal learning in social contexts, which elucidate how interaction with others influences causal learning. First, we consider children's explanation-seeking behaviors in the form of "why" questions. Second, we examine parents' elaboration of meaning about causal relations. Finally, we consider parents' interactive styles with children during free play, which constrains how children explore. We propose that the best way to understand children's causal learning in social context is to combine results from laboratory and natural interactive informal learning environments.

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

PubMed

Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

2018-03-29

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

'Complexity-compatible' policy for integrated care? Lessons from the implementation of Ontario's Health Links.

PubMed

Grudniewicz, Agnes; Tenbensel, Tim; Evans, Jenna M; Steele Gray, Carolyn; Baker, G Ross; Wodchis, Walter P

2018-02-01

Complex adaptive systems (CAS) theory views healthcare as numerous sub-systems characterized by diverse agents that interact, self-organize, and continuously adapt. We apply this complexity science perspective to examine the extent to which CAS theory is a useful lens for designing and implementing health policies. We present the case of Health Links, a "low rules" policy intervention in Ontario, Canada aimed at stimulating the development of voluntary networks of health and social organizations to improve care coordination for the most frequent users of the healthcare system. Our sample consisted of stakeholders from regional governance bodies and organizations partnering in Health Links. Qualitative interview data were coded using the key complexity concepts of sensemaking, self-organization, interconnections, coevolution, and emergence. We found that the complexity-compatible policy design successfully stimulated local dynamics of flexibility, experimentation, and learning and that important mediating factors include leadership, readiness, relationship-building, role clarity, communication, and resources. However, we saw tensions between preferences for flexibility and standardization. Desirable developments occurred only in some settings and failed to flow upward to higher levels, resulting in a piecemeal and patchy landscape. Attention needs to be paid not only to local dynamics and processes, but also to regional and provincial levels to ensure that learning flows to the top and informs decision-making. We conclude that implementation of complexity-compatible policies needs a balance between flexibility and consistency and the right leadership to coordinate the two. Complexity-compatible policy for integrated healthcare is more than simply 'letting a thousand flowers bloom'. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rivers are social–ecological systems: Time to integrate human dimensions into riverscape ecology and management

USGS Publications Warehouse

Dunham, Jason B.; Angermeier, Paul L.; Crausbay, Shelley D.; Cravens, Amanda; Gosnell, Hannah; McEvoy, Jamie; Moritz, Max A.; Raheem, Nejem; Sanford, Todd

2018-01-01

Incorporation of concepts from landscape ecology into understanding and managing riverine ecosystems has become widely known as riverscape ecology. Riverscape ecology emphasizes interactions among processes at different scales and their consequences for valued ecosystem components, such as riverine fishes. Past studies have focused strongly on understanding the ecological processes in riverscapes and how human actions modify those processes. It is increasingly clear, however, that an understanding of the drivers behind actions that lead to human modification also merit consideration, especially regarding how those drivers influence management efficacy. These indirect drivers of riverscape outcomes can be understood in the context of a diverse array of social processes, which we collectively refer to as human dimensions. Like ecological phenomena, social processes also exhibit complex interactions across spatiotemporal scales. Greater emphasis on feedbacks between social and ecological processes will lead scientists and managers to more completely understand riverscapes as complex, dynamic, interacting social–ecological systems. Emerging applications in riverscapes, as well as studies of other ecosystems, provide examples that can lead to stronger integration of social and ecological science. We argue that conservation successes within riverscapes may not come from better ecological science, improved ecosystem service analyses, or even economic incentives if the fundamental drivers of human behaviors are not understood and addressed in conservation planning and implementation.

Have we seen the geneticisation of society? Expectations and evidence.

PubMed

Weiner, Kate; Martin, Paul; Richards, Martin; Tutton, Richard

2017-09-01

Abby Lippman's geneticisation thesis, of the early 1990s, argued and anticipated that with the rise of genetics, increasing areas of social and health related activities would come to be understood and defined in genetic terms leading to major changes in society, medicine and health care. We review the considerable literature on geneticisation and consider how the concept stands both theoretically and empirically across scientific, clinical, popular and lay discourse and practice. Social science scholarship indicates that relatively little of the original claim of the geneticisation thesis has been realised, highlighting the development of more complex and dynamic accounts of disease in scientific discourse and the complexity of relationships between bioscientific, clinical and lay understandings. This scholarship represents a shift in social science understandings of the processes of sociotechnical change, which have moved from rather simplistic linear models to an appreciation of disease categories as multiply understood. Despite these shifts, we argue that a genetic imaginary persists, which plays a performative role in driving investments in new gene-based developments. Understanding the enduring power of this genetic imaginary and its consequences remains a key task for the social sciences, one which treats ongoing genetic expectations and predictions in a sceptical yet open way. © 2017 The Authors. Sociology of Health & Illness published by John Wiley & Sons Ltd on behalf of Foundation for SHIL.

Efficient and resilient governance of social-ecological systems.

PubMed

Erickson, Adam

2015-09-01

New institutions are critically needed to improve the resilience of social-ecological systems globally. Watershed management offers an important model due to its ability to govern mixed-ownership landscapes through common property regimes, translating national goals into local action. Here, I assess the efficacy of state watershed management institutions in the Pacific Northwest, based on their ability to support local watershed groups. I use document analysis to describe and compare state institutions in Washington, Oregon, Idaho, and California. Results indicate that state institutional efficiency and resilience are the key factors determining watershed group activity and stability. The primary drivers of institutional efficiency and resilience were institutional unification, robust funding portfolios, low agency conflict, and strong support for economic multiplier effects, creative partnerships, and scholarly research. My findings elucidate the critical role of institutional efficiency and resilience in governing dynamic and complex social-ecological systems, enabling the flexibility to address emergent transformations.

Critical Race Theory, Race Equity, and Public Health: Toward Antiracism Praxis

PubMed Central

Airhihenbuwa, Collins O.

2010-01-01

Racial scholars argue that racism produces rates of morbidity, mortality, and overall well-being that vary depending on socially assigned race. Eliminating racism is therefore central to achieving health equity, but this requires new paradigms that are responsive to structural racism's contemporary influence on health, health inequities, and research. Critical Race Theory is an emerging transdisciplinary, race-equity methodology that originated in legal studies and is grounded in social justice. Critical Race Theory's tools for conducting research and practice are intended to elucidate contemporary racial phenomena, expand the vocabulary with which to discuss complex racial concepts, and challenge racial hierarchies. We introduce Critical Race Theory to the public health community, highlight key Critical Race Theory characteristics (race consciousness, emphases on contemporary societal dynamics and socially marginalized groups, and praxis between research and practice) and describe Critical Race Theory's contribution to a study on racism and HIV testing among African Americans. PMID:20147679

Agonias: the social and sacred suffering of Azorean immigrants.

PubMed

James, Susan

2002-03-01

Agonias, meaning "the agonies," is a culture-specific somatic phenomenon experienced by Azorean immigrants. Although the community's health providers conceptualize agonias as an "anxiety disorder," interviews with community members revealed a more complex phenomenon. For them, agonias is a somatomoral experience--where the somatic, the social, the religious and the moral are inextricably linked. Because agonias connects things that, from the traditional medical perspective, should not be connected, such as mind, body, spirit, and community, it defies our psychiatric categorisation and goes beyond disciplinary boundaries. Agonias is a dynamic multivocal symbol that is not just an inanimate signifier but also a therapeutic act. On an individual level, it connects the sufferer with others and with God, transforming the interpersonal and divine space. On the societal level, it connects a community, losing its way of life, to the past and to its identity, preserving its social and religious traditions.

Attacked ravens flexibly adjust signalling behaviour according to audience composition.

PubMed

Szipl, Georgine; Ringler, Eva; Bugnyar, Thomas

2018-06-13

A fundamental attribute of social intelligence is the ability to monitor third-party relationships, which has been repeatedly demonstrated in primates, and recently also in captive ravens. It is yet unknown how ravens make use of this ability when dealing with different types of social relationships simultaneously during complex real-life situations. Free-ranging non-breeder ravens live in societies characterized by high fission-fusion dynamics and structured by age, pair-bond status and kinship. Here, we show that free-ranging ravens modify communication during conflicts according to audience composition. When being attacked by dominant conspecifics, victims of aggression signal their distress via defensive calls. Victims increased call rates when their kin were in the bystander audience, but reduced call rates when the bystanders were bonding partners of their aggressors. Hence, ravens use social knowledge flexibly and probably based on their own need (i.e. alert nearby allies and avoid alerting nearby rivals). © 2018 The Authors.

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants

PubMed Central

Hogan, Bernie; Melville, Joshua R.; Philips, Gregory Lee; Janulis, Patrick; Contractor, Noshir; Mustanski, Brian S.; Birkett, Michelle

2016-01-01

While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within–subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks. PMID:28018995

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants.

PubMed

Hogan, Bernie; Melville, Joshua R; Philips, Gregory Lee; Janulis, Patrick; Contractor, Noshir; Mustanski, Brian S; Birkett, Michelle

2016-05-01

While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within-subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks.

Trends in Social Science: The Impact of Computational and Simulative Models

NASA Astrophysics Data System (ADS)

Conte, Rosaria; Paolucci, Mario; Cecconi, Federico

This paper discusses current progress in the computational social sciences. Specifically, it examines the following questions: Are the computational social sciences exhibiting positive or negative developments? What are the roles of agent-based models and simulation (ABM), network analysis, and other "computational" methods within this dynamic? (Conte, The necessity of intelligent agents in social simulation, Advances in Complex Systems, 3(01n04), 19-38, 2000; Conte 2010; Macy, Annual Review of Sociology, 143-166, 2002). Are there objective indicators of scientific growth that can be applied to different scientific areas, allowing for comparison among them? In this paper, some answers to these questions are presented and discussed. In particular, comparisons among different disciplines in the social and computational sciences are shown, taking into account their respective growth trends in the number of publication citations over the last few decades (culled from Google Scholar). After a short discussion of the methodology adopted, results of keyword-based queries are presented, unveiling some unexpected local impacts of simulation on the takeoff of traditionally poorly productive disciplines.

The cultural production of health inequalities: a cross-sectional, multilevel examination of 52 countries.

PubMed

Mansyur, Carol Leler; Amick, Benjamin C; Harrist, Ronald B; Franzini, Luisa; Roberts, Robert E

2009-01-01

In a 2001 report, the U.S. National Institutes of Health called for more integration of the social sciences into health-related research, including research guided by theories and methods that take social and cultural systems into consideration. Based on a theoretical framework that integrates Hofstede's cultural dimensions with sociological theory, the authors used multilevel modeling to explore the association of culture with structural inequality and health disparities. Their results support the idea that cultural dimensions and social structure, along with economic development, may account for much of the cross-national variation in the distribution of health inequalities. Sensitivity tests also suggest that an interaction between culture and social structure may confound the relationship between income inequality and health. It is necessary to identify important cultural and social structural characteristics before we can achieve an understanding of the complex, dynamic systems that affect health, and develop culturally sensitive interventions and policies. This study takes a step toward identifying some of the relevant cultural and structural influences. More research is needed to explore the pathways leading from the sociocultural environment to health inequalities.

Ecology of zoonotic infectious diseases in bats: current knowledge and future directions

USGS Publications Warehouse

Hayman, D.T.; Bowen, R.A.; Cryan, P.M.; McCracken, G.F.; O'Shea, T.J.; Peel, A.J.; Gilbert, A.; Webb, C.T.; Wood, J.L.

2013-01-01

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics.

Ecology of Zoonotic Infectious Diseases in Bats: Current Knowledge and Future Directions

PubMed Central

Hayman, D T S; Bowen, R A; Cryan, P M; McCracken, G F; O’Shea, T J; Peel, A J; Gilbert, A; Webb, C T; Wood, J L N

2013-01-01

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics. PMID:22958281

Studies on the population dynamics of a rumor-spreading model in online social networks

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

Brains, brawn and sociality: a hyaena’s tale

PubMed Central

Holekamp, Kay E.; Dantzer, Ben; Stricker, Gregory; Shaw Yoshida, Kathryn C.; Benson-Amram, Sarah

2015-01-01

Theoretically intelligence should evolve to help animals solve specific types of problems posed by the environment, but it remains unclear how environmental complexity or novelty facilitates the evolutionary enhancement of cognitive abilities, or whether domain-general intelligence can evolve in response to domain-specific selection pressures. The social complexity hypothesis, which posits that intelligence evolved to cope with the labile behaviour of conspecific group-mates, has been strongly supported by work on the sociocognitive abilities of primates and other animals. Here we review the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas, and describe our tests of predictions of the social complexity hypothesis in regard to both cognition and brain size in hyaenas. Behavioural data indicate that there has been remarkable convergence between primates and hyaenas with respect to their abilities in the domain of social cognition. Furthermore, within the family Hyaenidae, our data suggest that social complexity might have contributed to enlargement of the frontal cortex. However, social complexity failed to predict either brain volume or frontal cortex volume in a larger array of mammalian carnivores. To address the question of whether or not social complexity might be able to explain the evolution of domain-general intelligence as well as social cognition in particular, we presented simple puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species housed in zoos and found that species with larger brains relative to their body mass were more innovative and more successful at opening the boxes. However, social complexity failed to predict success in solving this problem. Overall our work suggests that, although social complexity enhances social cognition, there are no unambiguous causal links between social complexity and either brain size or performance in problem-solving tasks outside the social domain in mammalian carnivores. PMID:26160980

Bayesian dynamical systems modelling in the social sciences.

PubMed

Ranganathan, Shyam; Spaiser, Viktoria; Mann, Richard P; Sumpter, David J T

2014-01-01

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

Investigating the Wicked Problems of (Un)sustainability Through Three Case Studies Around the Water-Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Metzger, E. P.; Curren, R. R.

2016-12-01

Effective engagement with the problems of sustainability begins with an understanding of the nature of the challenges. The entanglement of interacting human and Earth systems produces solution-resistant dilemmas that are often portrayed as wicked problems. As introduced by urban planners Rittel and Webber (1973), wicked problems are "dynamically complex, ill-structured, public problems" arising from complexity in both biophysical and socio-economic systems. The wicked problem construct is still in wide use across diverse contexts, disciplines, and sectors. Discourse about wicked problems as related to sustainability is often connected to discussion of complexity or complex systems. In preparation for life and work in an uncertain, dynamic and hyperconnected world, students need opportunities to investigate real problems that cross social, political and disciplinary divides. They need to grapple with diverse perspectives and values, and collaborate with others to devise potential solutions. Such problems are typically multi-casual and so intertangled with other problems that they cannot be resolved using the expertise and analytical tools of any single discipline, individual, or organization. We have developed a trio of illustrative case studies that focus on energy, water and food, because these resources are foundational, interacting, and causally connected in a variety of ways with climate destabilization. The three interrelated case studies progress in scale from the local and regional, to the national and international and include: 1) the 2010 Gulf of Mexico oil spill with examination of the multiple immediate and root causes of the disaster, its ecological, social, and economic impacts, and the increasing risk and declining energy return on investment associated with the relentless quest for fossil fuels; 2) development of Australia's innovative National Water Management System; and 3) changing patterns of food production and the intertwined challenge of managing transnational water resources in the rapidly growing Mekong Region of Southeast Asia. .

Evolution of the social network of scientific collaborations

NASA Astrophysics Data System (ADS)

Barabási, A. L.; Jeong, H.; Néda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T.

2002-08-01

The co-authorship network of scientists represents a prototype of complex evolving networks. In addition, it offers one of the most extensive database to date on social networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an 8-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. Three complementary approaches allow us to obtain a detailed characterization. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. In some limits the model can be solved analytically, predicting a two-regime scaling in agreement with the measurements. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically. The combined numerical and analytical results underline the important role internal links play in determining the observed scaling behavior and network topology. The results and methodologies developed in the context of the co-authorship network could be useful for a systematic study of other complex evolving networks as well, such as the world wide web, Internet, or other social networks.

Live interaction distinctively shapes social gaze dynamics in rhesus macaques.

PubMed

Dal Monte, Olga; Piva, Matthew; Morris, Jason A; Chang, Steve W C

2016-10-01

The dynamic interaction of gaze between individuals is a hallmark of social cognition. However, very few studies have examined social gaze dynamics after mutual eye contact during real-time interactions. We used a highly quantifiable paradigm to assess social gaze dynamics between pairs of monkeys and modeled these dynamics using an exponential decay function to investigate sustained attention after mutual eye contact. When monkeys were interacting with real partners compared with static images and movies of the same monkeys, we found a significant increase in the proportion of fixations to the eyes and a smaller dispersion of fixations around the eyes, indicating enhanced focal attention to the eye region. Notably, dominance and familiarity between the interacting pairs induced separable components of gaze dynamics that were unique to live interactions. Gaze dynamics of dominant monkeys after mutual eye contact were associated with a greater number of fixations to the eyes, whereas those of familiar pairs were associated with a faster rate of decrease in this eye-directed attention. Our findings endorse the notion that certain key aspects of social cognition are only captured during interactive social contexts and dependent on the elapsed time relative to socially meaningful events. Copyright © 2016 the American Physiological Society.

Live interaction distinctively shapes social gaze dynamics in rhesus macaques

PubMed Central

Piva, Matthew; Morris, Jason A.; Chang, Steve W. C.

2016-01-01

The dynamic interaction of gaze between individuals is a hallmark of social cognition. However, very few studies have examined social gaze dynamics after mutual eye contact during real-time interactions. We used a highly quantifiable paradigm to assess social gaze dynamics between pairs of monkeys and modeled these dynamics using an exponential decay function to investigate sustained attention after mutual eye contact. When monkeys were interacting with real partners compared with static images and movies of the same monkeys, we found a significant increase in the proportion of fixations to the eyes and a smaller dispersion of fixations around the eyes, indicating enhanced focal attention to the eye region. Notably, dominance and familiarity between the interacting pairs induced separable components of gaze dynamics that were unique to live interactions. Gaze dynamics of dominant monkeys after mutual eye contact were associated with a greater number of fixations to the eyes, whereas those of familiar pairs were associated with a faster rate of decrease in this eye-directed attention. Our findings endorse the notion that certain key aspects of social cognition are only captured during interactive social contexts and dependent on the elapsed time relative to socially meaningful events. PMID:27486105

Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems

PubMed Central

Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D. Y.

2016-01-01

Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language. PMID:28006026

Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems.

PubMed

Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D Y; Ivanov, Plamen Ch

2016-01-01

Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

Applying the Dynamic Social Systems Model to HIV prevention in a rural African context: The Maasai and the esoto dance

PubMed Central

Siegler, Aaron J.; Mbwambo, Jessie K.; DiClemente, Ralph J.

2013-01-01

This study applied the Dynamic Social Systems Model (DSSM) to the issue of HIV risk among the Maasai tribe of Tanzania, using data from a cross-sectional, cluster survey among 370 randomly selected participants from Ngorongoro and Siha Districts. A culturally-appropriate survey instrument was developed to explore traditions reportedly coadunate with sexual partnership, including “wife-sharing”, fertility rituals, and various traditional dances. One dance, esoto, accounted for over two-thirds of participants’ lifetime sexual partners (n=10.5). The DSSM, combining structural and systems theories, was applied to systematize complex multilevel factors regarding esoto practice. Participants reported multifaceted beliefs regarding esoto; a majority viewed the dance as exciting and essential, yet most men feared social stigma and three-quarters of women had experienced physical punishment for non-attendance. In multivariate logistic regression, esoto attendance was predicted by female gender (AOR 4.67, 95% CI: 1.6, 13.2), higher positive beliefs regarding esoto (AOR 2.84, 95% CI: 1.9, 4.2) and Maasai lifecycle events (AOR 0.06, 95% CI: 0.01, 0.47). The DSSM proved useful for characterizing esoto and for revealing feedback loops that maintain esoto, thus indicating avenues for future interventions. PMID:23372030

Interpreting participatory Fuzzy Cognitive Maps as complex networks in the social-ecological systems of the Amazonian forests

NASA Astrophysics Data System (ADS)

Varela, Consuelo; Tarquis, Ana M.; Blanco-Gutiérrez, Irene; Estebe, Paloma; Toledo, Marisol; Martorano, Lucieta

2015-04-01

Social-ecological systems are linked complex systems that represent interconnected human and biophysical processes evolving and adapting across temporal and spatial scales. In the real world, social-ecological systems pose substantial challenges for modeling. In this regard, Fuzzy Cognitive Maps (FCMs) have proven to be a useful method for capturing the functioning of this type of systems. FCMs are a semi-quantitative type of cognitive map that represent a system composed of relevant factors and weighted links showing the strength and direction of cause-effects relationships among factors. Therefore, FCMs can be interpreted as complex system structures or complex networks. In this sense, recent research has applied complex network concepts for the analysis of FCMs that represent social-ecological systems. Key to FCM the tool is its potential to allow feedback loops and to include stakeholder knowledge in the construction of the tool. Also, previous research has demonstrated their potential to represent system dynamics and simulate the effects of changes in the system, such as policy interventions. For illustrating this analysis, we have developed a series of participatory FCM for the study of the ecological and human systems related to biodiversity conservation in two case studies of the Amazonian region, the Bolivia lowlands of Guarayos and the Brazil Tapajos National forest. The research is carried out in the context of the EU project ROBIN1 and it is based on the development of a series of stakeholder workshops to analyze the current state of the socio-ecological environment in the Amazonian forest, reflecting conflicts and challenges for biodiversity conservation and human development. Stakeholders included all relevant actors in the local case studies, namely farmers, environmental groups, producer organizations, local and provincial authorities and scientists. In both case studies we illustrate the use of complex networks concepts, such as the adjacency matrix and centrality properties (e.g.: centrality, page-rank, betweenness centrality). Different measures of network centrality evidence that deforestation and loss of biodiversity are the most relevant factors in the FCM of the two case studies analyzed. In both cases agricultural expansion emerges as a key driver of deforestation. The lack of policy coordination and a weak implementation and enforcement are also highly influential factors. The analysis of the system's dynamics suggest that in the case of Bolivia forest fires and deforestation are likely to continue in the immediate future as illegal activities are maintained and poverty increases. In the case of Brazil a decrease in available viable economic activities is driving further deforestation and ecosystem services loss. Overall, the research evidences how using FCMs together with complex network analysis can support policy development by identifying key elements and processes upon which policy makers and institutions can take action. Acknowledgements The authors would like to acknowledge the EU project ROBIN (The Role of Biodiversity in Climate Change Mitigation, from the EC FP7, no 283093) and the Spanish project AL14-PID-12 (Biodiversidad y cambio climático en la Amazonía: Perspectivas socio-económicas y ambientales) of the UPM Latin America Cooperation Program for funding this research.

From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

NASA Astrophysics Data System (ADS)

Saramäki, Jari; Moro, Esteban

2015-06-01

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

The many faces of graph dynamics

NASA Astrophysics Data System (ADS)

Pignolet, Yvonne Anne; Roy, Matthieu; Schmid, Stefan; Tredan, Gilles

2017-06-01

The topological structure of complex networks has fascinated researchers for several decades, resulting in the discovery of many universal properties and reoccurring characteristics of different kinds of networks. However, much less is known today about the network dynamics: indeed, complex networks in reality are not static, but rather dynamically evolve over time. Our paper is motivated by the empirical observation that network evolution patterns seem far from random, but exhibit structure. Moreover, the specific patterns appear to depend on the network type, contradicting the existence of a ‘one fits it all’ model. However, we still lack observables to quantify these intuitions, as well as metrics to compare graph evolutions. Such observables and metrics are needed for extrapolating or predicting evolutions, as well as for interpolating graph evolutions. To explore the many faces of graph dynamics and to quantify temporal changes, this paper suggests to build upon the concept of centrality, a measure of node importance in a network. In particular, we introduce the notion of centrality distance, a natural similarity measure for two graphs which depends on a given centrality, characterizing the graph type. Intuitively, centrality distances reflect the extent to which (non-anonymous) node roles are different or, in case of dynamic graphs, have changed over time, between two graphs. We evaluate the centrality distance approach for five evolutionary models and seven real-world social and physical networks. Our results empirically show the usefulness of centrality distances for characterizing graph dynamics compared to a null-model of random evolution, and highlight the differences between the considered scenarios. Interestingly, our approach allows us to compare the dynamics of very different networks, in terms of scale and evolution speed.

Real-time path planning in dynamic virtual environments using multiagent navigation graphs.

PubMed

Sud, Avneesh; Andersen, Erik; Curtis, Sean; Lin, Ming C; Manocha, Dinesh

2008-01-01

We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multi-agent Navigation Graph (MaNG), which is constructed using first- and second-order Voronoi diagrams. The MaNG is used to perform route planning and proximity computations for each agent in real time. Moreover, we use the path information and proximity relationships for local dynamics computation of each agent by extending a social force model [Helbing05]. We compute the MaNG using graphics hardware and present culling techniques to accelerate the computation. We also address undersampling issues and present techniques to improve the accuracy of our algorithm. Our algorithm is used for real-time multi-agent planning in pursuit-evasion, terrain exploration and crowd simulation scenarios consisting of hundreds of moving agents, each with a distinct goal.

Team Learning: New Insights Through a Temporal Lens.

PubMed

Lehmann-Willenbrock, Nale

2017-04-01

Team learning is a complex social phenomenon that develops and changes over time. Hence, to promote understanding of the fine-grained dynamics of team learning, research should account for the temporal patterns of team learning behavior. Taking important steps in this direction, this special issue offers novel insights into the dynamics of team learning by advocating a temporal perspective. Based on a symposium presented at the 2016 Interdisciplinary Network for Group Research (INGRoup) Conference in Helsinki, the four empirical articles in this special issue showcase four different and innovative approaches to implementing a temporal perspective in team learning research. Specifically, the contributions highlight team learning dynamics in student teams, self-managing teams, teacher teams, and command and control teams. The articles cover a broad range of methods and designs, including both qualitative and quantitative methodologies, and longitudinal as well as micro-temporal approaches. The contributors represent four countries and five different disciplines in group research.

[Dynamic psychology and psychoanalysis in Giovanni Jervis' thought].

PubMed

Dazzi, Nino

2012-01-01

As against the background of an unconditioned reception of Darwinian theory and its developments, mainly in the field of ethology, a reflection deploys itself on complex theoretical themes, such as identity, consciousness and motivation. This leads Jervis to deal not only and not as much with psychoanalysis, as with a broader theoretical framework, labelled as "dynamic psychology". Contributions from different fields of contemporary psychological knowledge, particularly from cognitive sciences, personality and social psychology and developmental observations converge into this new framework. A proposal is made that is characterized by a peculiar critical sensitivity and is open to future developments. It is in this new light that Jervis was able to carry out a retrospective recognition of the century of Psychoanalysis.

A system dynamics approach for integrated management of the Jucar River Basin

NASA Astrophysics Data System (ADS)

Rubio-Martin, Adria; Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

2017-04-01

System dynamics (SD) is a modelling approach that allows the analysis of complex systems through the mathematical definition of variables and their relationships. Based on systems thinking, SD is suitable for interdisciplinary studies of the management of complex systems. Over the past 50 years, SD tools have been applied to fields as diverse as economics, ecology, politics, sociology and resource management. Its application to the field of water resources has grown significantly over the last two decades, facilitating the enhancement of models by adding social, economic and ecological components. However, its application to the operation of complex multireservoir systems has been very limited so far. In this contribution, we have developed a SD model for the Jucar River Basin, one of the most vulnerable basins in the western Mediterranean region with regard to droughts. The system has three main reservoirs, which allows for a multiannual management of the storage that compensates the highly variable streamflow from upstream. Our SD model of the Jucar River Basin is able to capture the complexity of the water resource system. The model developed consists of five interlinked subsystems: a) Topology of the system network, including the 3 main reservoirs, water seepage and evaporation, inflows and catchments. b) Monthly operating rules of each reservoir. The rules were derived from the expert knowledge eluded from the operators of the reservoirs. c) Monthly urban, agricultural and environmental water demands. d) State index of the system and drought mitigation measures triggered depending on the state index. e) Mancha Oriental aquifer and stream-aquifer interaction with the Jucar River. The comparison between observed and simulated series showed that the model provides a good representation of the observed reservoir operation and total deficits. The interdisciplinary and open nature of the methodology allows to add new variables and dynamics to the model that are rooted on non-physical system components, including management (operating rules), political (drought mitigation measures), and social (population growth) aspects. The structure-behaviour link of SD models allows analysis of how changes in one part of the system might affect the behaviour of the system as a whole. This allows testing how the system will respond under varying sets of conditions, including climate change scenarios. ACKNOWLEDGEMENTS This study has been supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with MINECO (Ministerio de Economía y Competitividad, España) and FEDER funds, the European Union's Horizon 2020 research and innovation programme under the IMPREX project (GA n. 641.811), and the Garantía Juvenil grants of the Ministerio Empleo y Seguridad Social, Spain.

Voting contagion: Modeling and analysis of a century of U.S. presidential elections

PubMed Central

de Aguiar, Marcus A. M.

2017-01-01

Social influence plays an important role in human behavior and decisions. Sources of influence can be divided as external, which are independent of social context, or as originating from peers, such as family and friends. An important question is how to disentangle the social contagion by peers from external influences. While a variety of experimental and observational studies provided insight into this problem, identifying the extent of contagion based on large-scale observational data with an unknown network structure remains largely unexplored. By bridging the gap between the large-scale complex systems perspective of collective human dynamics and the detailed approach of social sciences, we present a parsimonious model of social influence, and apply it to a central topic in political science—elections and voting behavior. We provide an analytical expression of the county vote-share distribution, which is in excellent agreement with almost a century of observed U.S. presidential election data. Analyzing the social influence topography over this period reveals an abrupt phase transition from low to high levels of social contagion, and robust differences among regions. These results suggest that social contagion effects are becoming more instrumental in shaping large-scale collective political behavior, with implications on democratic electoral processes and policies. PMID:28542409

Detection of social group instability among captive rhesus macaques using joint network modeling

PubMed Central

Beisner, Brianne A.; Jin, Jian; Fushing, Hsieh; Mccowan, Brenda

2015-01-01

Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We used a joint network modeling approach to examine the interdependencies between two behavioral networks, aggression and status signaling, from four stable and three unstable groups of rhesus macaques in order to identify characteristic patterns of network interdependence in stable groups that are readily distinguishable from unstable groups. Our results showed that the most prominent source of aggression-status network interdependence in stable social groups came from more frequent dyads than expected with opposite direction status-aggression (i.e. A threatens B and B signals acceptance of subordinate status). In contrast, unstable groups showed a decrease in opposite direction aggression-status dyads (but remained higher than expected) as well as more frequent than expected dyads with bidirectional aggression. These results demonstrate that not only was the stable joint relationship between aggression and status networks readily distinguishable from unstable time points, social instability manifested in at least two different ways. In sum, our joint modeling approach may prove useful in quantifying and monitoring the complex social dynamics of any wild or captive social system, as all social systems are composed of multiple interconnected networks PMID:26052339

How Social Structure Drives the Population Dynamics of the Common Vampire Bat (Desmodus rotundus, Phyllostomidae).

PubMed

Huguin, Maïlis; Arechiga-Ceballos, Nidia; Delaval, Marguerite; Guidez, Amandine; de Castro, Isaï Jorge; Lacoste, Vincent; Salmier, Arielle; Setién, Alvaro Aguilar; Silva, Claudia Regina; Lavergne, Anne; de Thoisy, Benoit

2018-05-11

Social systems are major drivers of population structure and gene flow, with important effects on dynamics and dispersal of associated populations of parasites. Among bats, the common vampire bat (Desmodus rotundus) has likely one of the most complex social structures. Using autosomal and mitochondrial markers on vampires from Mexico, French Guiana, and North Brazil, from both roosting and foraging areas, we observed an isolation by distance at the wider scale and lower but significant differentiation between closer populations (<50 km). All populations had a low level of relatedness and showed deviations from Hardy-Weinberg equilibrium and a low but significant inbreeding coefficient. The associated heterozygote deficiency was likely related to a Wahlund effect and to cryptic structures, reflecting social groups living in syntopy, both in roosting and foraging areas, with only limited admixture. Discrepancy between mitochondrial and nuclear markers suggests female philopatry and higher dispersal rates in males, associated with peripheral positions in the groups. Vampires are also the main neotropical reservoir for rabies virus, one of the main lethal pathogens for humans. Female social behaviors and trophallaxis may favor a rapid spread of virus to related and unrelated offspring and females. The high dispersal capacity of males may explain the wider circulation of viruses and the inefficacy of bat population controls. In such opportunistic species, gene connectivity should be considered for management decision making. Strategies such as culling could induce immigration of bats from neighboring colonies to fill vacant roosts and feeding areas, associated with the dispersal of viral strains.

Information-theoretic metamodel of organizational evolution

NASA Astrophysics Data System (ADS)

Sepulveda, Alfredo

2011-12-01

Social organizations are abstractly modeled by holarchies---self-similar connected networks---and intelligent complex adaptive multiagent systems---large networks of autonomous reasoning agents interacting via scaled processes. However, little is known of how information shapes evolution in such organizations, a gap that can lead to misleading analytics. The research problem addressed in this study was the ineffective manner in which classical model-predict-control methods used in business analytics attempt to define organization evolution. The purpose of the study was to construct an effective metamodel for organization evolution based on a proposed complex adaptive structure---the info-holarchy. Theoretical foundations of this study were holarchies, complex adaptive systems, evolutionary theory, and quantum mechanics, among other recently developed physical and information theories. Research questions addressed how information evolution patterns gleamed from the study's inductive metamodel more aptly explained volatility in organization. In this study, a hybrid grounded theory based on abstract inductive extensions of information theories was utilized as the research methodology. An overarching heuristic metamodel was framed from the theoretical analysis of the properties of these extension theories and applied to business, neural, and computational entities. This metamodel resulted in the synthesis of a metaphor for, and generalization of organization evolution, serving as the recommended and appropriate analytical tool to view business dynamics for future applications. This study may manifest positive social change through a fundamental understanding of complexity in business from general information theories, resulting in more effective management.

The impact of emotional faces on social motivation in schizophrenia.

PubMed

Radke, Sina; Pfersmann, Vera; Derntl, Birgit

2015-10-01

Impairments in emotion recognition and psychosocial functioning are a robust phenomenon in schizophrenia and may affect motivational behavior, particularly during socio-emotional interactions. To characterize potential deficits and their interplay, we assessed social motivation covering various facets, such as implicit and explicit approach-avoidance tendencies to facial expressions, in 27 patients with schizophrenia (SZP) and 27 matched healthy controls (HC). Moreover, emotion recognition abilities as well as self-reported behavioral activation and inhibition were evaluated. Compared to HC, SZP exhibited less pronounced approach-avoidance ratings to happy and angry expressions along with prolonged reactions during automatic approach-avoidance. Although deficits in emotion recognition were replicated, these were not associated with alterations in social motivation. Together with additional connections between psychopathology and several approach-avoidance processes, these results identify motivational impairments in SZP and suggest a complex relationship between different aspects of social motivation. In the context of specialized interventions aimed at improving social cognitive abilities in SZP, the link between such dynamic measures, motivational profiles and functional outcomes warrants further investigations, which can provide important leverage points for treatment. Crucially, our findings present first insights into the assessment and identification of target features of social motivation.

Study on the Reduced Traffic Congestion Method Based on Dynamic Guidance Information

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Wang, Guang-Min; Wang, Tao; Ren, Hua-Ling; Zhang, Lin

2018-05-01

This paper studies how to generate the reasonable information of travelers’ decision in real network. This problem is very complex because the travelers’ decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD (Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately. A consistency algorithm is designed to investigate the travelers’ decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further, a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance. Supported by National Natural Science Foundation of China under Grant Nos. 71471104, 71771019, 71571109, and 71471167; The University Science and Technology Program Funding Projects of Shandong Province under Grant No. J17KA211; The Project of Public Security Department of Shandong Province under Grant No. GATHT2015-236; The Major Social and Livelihood Special Project of Jinan under Grant No. 20150905

Extended quantification of the generalized recurrence plot

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2016-04-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing structures, turbulent spatial plankton patterns, and fractals. But, it is also successfully applied to the description of spatio-temporal dynamics and the detection of regime shifts, such as in the complex Ginzburg-Landau- equation. The recurrence plot based determinism is a central measure in this framework quantifying the level of regularities in temporal and spatial structures. We extend this measure for the generalized recurrence plot considering additional operations of symmetry than the simple translation. It is tested not only on two-dimensional regular patterns and noise but also on complex spatial patterns reconstructing the parameter space of the complex Ginzburg-Landau-equation. The extended version of the determinism resulted in values which are consistent to the original recurrence plot approach. Furthermore, the proposed method allows a split of the determinism into parts which based on laminar and non-laminar regions of the two-dimensional pattern of the complex Ginzburg-Landau-equation. A comparison of these parts with a standard method of image classification, the co-occurrence matrix approach, shows differences especially in the description of patterns associated with turbulence. In that case, it seems that the extended version of the determinism allows a distinction of phase turbulence and defect turbulence by means of their spatial patterns. This ability of the proposed method promise new insights in other systems with turbulent dynamics coming from climatology, biology, ecology, and social sciences, for example.

Integrating GIS and ABM to Explore Spatiotemporal Dynamics

NASA Astrophysics Data System (ADS)

Sun, M.; Jiang, Y.; Yang, C.

2013-12-01

Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.

Hybrid function projective synchronization in complex dynamical networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Qiang; Wang, Xing-yuan, E-mail: wangxy@dlut.edu.cn; Hu, Xiao-peng

2014-02-15

This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

Is sociality required for the evolution of communicative complexity? Evidence weighed against alternative hypotheses in diverse taxonomic groups

PubMed Central

Ord, Terry J.; Garcia-Porta, Joan

2012-01-01

Complex social communication is expected to evolve whenever animals engage in many and varied social interactions; that is, sociality should promote communicative complexity. Yet, informal comparisons among phylogenetically independent taxonomic groups seem to cast doubt on the putative role of social factors in the evolution of complex communication. Here, we provide a formal test of the sociality hypothesis alongside alternative explanations for the evolution of communicative complexity. We compiled data documenting variations in signal complexity among closely related species for several case study groups—ants, frogs, lizards and birds—and used new phylogenetic methods to investigate the factors underlying communication evolution. Social factors were only implicated in the evolution of complex visual signals in lizards. Ecology, and to some degree allometry, were most likely explanations for complexity in the vocal signals of frogs (ecology) and birds (ecology and allometry). There was some evidence for adaptive evolution in the pheromone complexity of ants, although no compelling selection pressure was identified. For most taxa, phylogenetic null models were consistently ranked above adaptive models and, for some taxa, signal complexity seems to have accumulated in species via incremental or random changes over long periods of evolutionary time. Becoming social presumably leads to the origin of social communication in animals, but its subsequent influence on the trajectory of signal evolution has been neither clear-cut nor general among taxonomic groups. PMID:22641820

A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems

NASA Astrophysics Data System (ADS)

Pöppl, Ronald; Keesstra, Saskia; Maroulis, Jerry

2017-04-01

Human-induced landscape change is difficult to predict due to the complexity inherent in both geomorphic and social systems as well as due to emerging coupling relationships between them. To better understand system complexity and system response to change, connectivity has become an important research paradigm within various disciplines including geomorphology, hydrology and ecology. With the proposed conceptual connectivity framework on geomorphic change in human-impacted fluvial systems a cautionary note is flagged regarding the need (i) to include and to systematically conceptualise the role of different types of human agency in altering connectivity relationships in geomorphic systems and (ii) to integrate notions of human-environment interactions to connectivity concepts in geomorphology to better explain causes and trajectories of landscape change. Underpinned by case study examples, the presented conceptual framework is able to explain how geomorphic response of fluvial systems to human disturbance is determined by system-specific boundary conditions (incl. system history, related legacy effects and lag times), vegetation dynamics and human-induced functional relationships (i.e. feedback mechanisms) between the different spatial dimensions of connectivity. It is further demonstrated how changes in social systems can trigger a process-response feedback loop between social and geomorphic systems that further governs the trajectory of landscape change in coupled human-geomorphic systems.

Leveraging percolation theory to single out influential spreaders in networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Castellano, Claudio

2016-06-01

Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading.

Results and Lessons Learned from a Coupled Social and Physical Hydrology Model: Testing Alternative Water Management Policies and Institutional Structures Using Agent-Based Modeling and Regional Hydrology

NASA Astrophysics Data System (ADS)

Murphy, J.; Lammers, R. B.; Prousevitch, A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Kliskey, A. D.; Alessa, L.

2015-12-01

Water Management in the U.S. Southwest is under increasing scrutiny as many areas endure persistent drought. The impact of these prolonged dry conditions is a product of regional climate and hydrological conditions, but also of a highly engineered water management infrastructure and a complex web of social arrangements whereby water is allocated, shared, exchanged, used, re-used, and finally consumed. We coupled an agent-based model with a regional hydrological model to understand the dynamics in one richly studied and highly populous area: southern Arizona, U.S.A., including metropolitan Phoenix and Tucson. There, multiple management entities representing an array of municipalities and other water providers and customers, including private companies and Native American tribes are enmeshed in a complex legal and economic context in which water is bought, leased, banked, and exchanged in a variety of ways and on multiple temporal and physical scales. A recurrent question in the literature of adaptive management is the impact of management structure on overall system performance. To explore this, we constructed an agent-based model to capture this social complexity, and coupled this with a physical hydrological model that we used to drive the system under a variety of water stress scenarios and to assess the regional impact of the social system's performance. We report the outcomes of ensembles of runs in which varieties of alternative policy constraints and management strategies are considered. We hope to contribute to policy discussions in this area and connected and legislatively similar areas (such as California) as current conditions change and existing legal and policy structures are revised. Additionally, we comment on the challenges of integrating models that ostensibly are in different domains (physical and social) but that independently represent a system in which physical processes and human actions are closely intertwined and difficult to disentangle.