The Social Living Complex: A New, All Day, Yearlong Intervention Model for Individuals with Autism Spectrum Disorder and Their Parents

ERIC Educational Resources Information Center

Doenyas, Ceymi

2016-01-01

We propose an unprecedented intervention for individuals with autism spectrum disorder (ASD) and their parents: the social living complex. Unlike existing social skills interventions, peer-mediated interventions here are not limited to the school/experiment duration and setting. Whereas other supported living services house adults with ASD only,…

A meme propagation model to combine social affirmation with meme attractiveness and persistence

NASA Astrophysics Data System (ADS)

Zheng, Aiguo; Luo, Shuangling; Xia, Haoxiang

2016-06-01

The propagation of memes on online social networks often depends on the mechanism of social affirmation. Centola termed such social-affirmation-driven diffusion as complex contagion and partly validated it through an online experiment. However, for actual online meme propagation, the mechanism of social affirmation often takes effect in combination with various other factors and mechanisms. In this paper, we examine the combinatorial effects of social affirmation and the attractiveness and persistence of the meme by proposing and analyzing a UACI model, where an agent’s activities to receive and transfer a meme is associated with the transition between its four possible states of “Uninformed”, “Attended”,“Convinced” and “Immune”. The numerical simulations illustrate nontrivial patterns of propagation. Especially, it is revealed that the effects of simple and complex contagions co-exist and equilibrate in accordance with the joint functions of meme attractiveness and social affirmation. Furthermore, the low-persistence of the meme hinders the propagation-scale more remarkably on the regular network than on the random one, indicating that the persistence may be critical for retaining complex contagion.

Organizational-economic model of formation of socio-commercial multifunctional complex in the construction of high-rise buildings

NASA Astrophysics Data System (ADS)

Kirillova, Ariadna; Prytkova, Oksana O.

2018-03-01

The article is devoted to the features of the formation of the organizational and economic model of the construction of a socio-commercial multifunctional complex for high-rise construction. Authors have given examples of high-altitude multifunctional complexes in Moscow, analyzed the advantages and disadvantages in the implementation of multifunctional complexes, stressed the need for a holistic strategic approach, allowing to take into account the prospects for the development of the city and the creation of a comfortable living environment. Based on the analysis of multifunctional complexes features, a matrix of SWOT analysis was compiled. For the development of cities and improving the quality of life of the population, it is proposed to implement a new type of multifunctional complexes of a joint social and commercial direction, including, along with the implementation of office areas - schools, polyclinics, various sports facilities and cultural and leisure centers (theatrical, dance, studio, etc.). The approach proposed in the article for developing the model is based on a comparative evaluation of the multifunctional complex project of a social and commercial direction implemented at the expense of public-private partnership in the form of a concession agreement and a commercial multifunctional complex being built at the expense of the investor. It has been proved by calculations that the obtained indicators satisfy the conditions of expediency of the proposed organizational-economic model and the project of the social and commercial multifunctional complex is effective.

From cultural traditions to cumulative culture: parameterizing the differences between human and nonhuman culture.

PubMed

Kempe, Marius; Lycett, Stephen J; Mesoudi, Alex

2014-10-21

Diverse species exhibit cultural traditions, i.e. population-specific profiles of socially learned traits, from songbird dialects to primate tool-use behaviours. However, only humans appear to possess cumulative culture, in which cultural traits increase in complexity over successive generations. Theoretically, it is currently unclear what factors give rise to these phenomena, and consequently why cultural traditions are found in several species but cumulative culture in only one. Here, we address this by constructing and analysing cultural evolutionary models of both phenomena that replicate empirically attestable levels of cultural variation and complexity in chimpanzees and humans. In our model of cultural traditions (Model 1), we find that realistic cultural variation between populations can be maintained even when individuals in different populations invent the same traits and migration between populations is frequent, and under a range of levels of social learning accuracy. This lends support to claims that putative cultural traditions are indeed cultural (rather than genetic) in origin, and suggests that cultural traditions should be widespread in species capable of social learning. Our model of cumulative culture (Model 2) indicates that both the accuracy of social learning and the number of cultural demonstrators interact to determine the complexity of a trait that can be maintained in a population. Combining these models (Model 3) creates two qualitatively distinct regimes in which there are either a few, simple traits, or many, complex traits. We suggest that these regimes correspond to nonhuman and human cultures, respectively. The rarity of cumulative culture in nature may result from this interaction between social learning accuracy and number of demonstrators. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Perceived Social Relationships and Science Learning Outcomes for Taiwanese Eighth Graders: Structural Equation Modeling with a Complex Sampling Consideration

ERIC Educational Resources Information Center

Jen, Tsung-Hau; Lee, Che-Di; Chien, Chin-Lung; Hsu, Ying-Shao; Chen, Kuan-Ming

2013-01-01

Based on the Trends in International Mathematics and Science Study 2007 study and a follow-up national survey, data for 3,901 Taiwanese grade 8 students were analyzed using structural equation modeling to confirm a social-relation-based affection-driven model (SRAM). SRAM hypothesized relationships among students' perceived social relationships in…

The social determinants of oral health: new approaches to conceptualizing and researching complex causal networks.

PubMed

Newton, J Timothy; Bower, Elizabeth J

2005-02-01

Oral epidemiological research into the social determinants of oral health has been limited by the absence of a theoretical framework which reflects the complexity of real life social processes and the network of causal pathways between social structure and oral health and disease. In the absence of such a framework, social determinants are treated as isolated risk factors, attributable to the individual, having a direct impact on oral health. There is little sense of how such factors interrelate over time and place and the pathways between the factors and oral health. Features of social life which impact on individuals' oral health but are not reducible to the individual remain under-researched. A conceptual framework informing mainstream epidemiological research into the social determinants of health is applied to oral epidemiology. The framework suggests complex causal pathways between social structure and health via interlinking material, psychosocial and behavioural pathways. Methodological implications for oral epidemiological research informed by the framework, such as the use of multilevel modelling, path analysis and structural equation modelling, combining qualitative and quantitative research methods, and collaborative research, are discussed. Copyright Blackwell Munksgaard, 2005.

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.

Interaction of mathematical modeling and social and behavioral HIV/AIDS research.

PubMed

Cassels, Susan; Goodreau, Steven M

2011-03-01

HIV is transmitted within complex biobehavioral systems. Mathematical modeling can provide insight to complex population-level outcomes of various behaviors measured at an individual level. HIV models in the social and behavioral sciences can be categorized in a number of ways; here, we consider two classes of applications common in the field generally, and in the past year in particular: those models that explore significant behavioral determinants of HIV disparities within and between populations; and those models that seek to evaluate the potential impact of specific social and behavioral interventions. We discuss two overarching issues we see in the field: the need to further systematize effectiveness models of behavioral interventions, and the need for increasing investigation of the use of behavioral data in epidemic models. We believe that a recent initiative by the National Institutes of Health will qualitatively change the relationships between epidemic modeling and sociobehavioral prevention research in the coming years.

Good practice in social care for disabled adults and older people with severe and complex needs: evidence from a scoping review.

PubMed

Gridley, Kate; Brooks, Jenni; Glendinning, Caroline

2014-05-01

This article reports findings from a scoping review of the literature on good practice in social care for disabled adults and older people with severe and complex needs. Scoping reviews differ from systematic reviews, in that they aim to rapidly map relevant literature across an area of interest. This review formed part of a larger study to identify social care service models with characteristics desired by people with severe and complex needs and scope the evidence of effectiveness. Systematic database searches were conducted for literature published between January 1997 and February 2011 on good practice in UK social care services for three exemplar groups: young adults with life-limiting conditions; adults who had suffered a brain injury or spinal injury and had severe or complex needs; and older people with dementia and complex needs. Five thousand and ninety-eight potentially relevant records were identified through electronic searching and 51 by hand. Eighty-six papers were selected for inclusion, from which 29 studies of specific services were identified. However, only four of these evaluated a service model against a comparison group and only six reported any evidence of costs. Thirty-five papers advocated person-centred support for people with complex needs, but no well-supported evaluation evidence was found in favour of any particular approach to delivering this. The strongest evaluation evidence indicated the effectiveness of a multidisciplinary specialist team for young adults; intensive case management for older people with advanced dementia; a specialist social worker with a budget for domiciliary care working with psycho-geriatric inpatients; and interprofessional training for community mental health professionals. The dearth of robust evaluation evidence identified through this review points to an urgent need for more rigorous evaluation of models of social care for disabled adults and older people with severe and complex needs. © 2013 John Wiley & Sons Ltd.

An Integrative Social-Cognitive Developmental Model of Supervision for Substance Abuse Counselors-in-Training

ERIC Educational Resources Information Center

Sias, Shari M.; Lambie, Glenn W.

2008-01-01

Substance abuse counselors (SACs) at higher levels of social-cognitive maturity manage complex situations and perform counselor-related tasks more effectively than individuals at lower levels of development. This article presents an integrative clinical supervision model designed to promote the social-cognitive maturity (ego development;…

Teaching Socially Expressive Behaviors to Children with Autism through Video Modeling

ERIC Educational Resources Information Center

Charlop, Marjorie H.; Dennis, Brian; Carpenter, Michael H.; Greenberg, Alissa L.

2010-01-01

Children with autism often lack complex socially expressive skills that would allow them to engage others more successfully. In the present study, video modeling was used to promote appropriate verbal comments, intonation, gestures, and facial expressions during social interactions of three children with autism. In baseline, the children rarely…

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

A Case Study of the Implementation of Social Models of Teaching in E-Learning: "The Social Networks in Education", Online Course of the Inter-Orthodox Centre of the Church of Greece

ERIC Educational Resources Information Center

Komninou, Ioanna

2018-01-01

The development of e-learning has caused a growing interest in learning models that may have the best results. We believe that it is good practice to implement social learning models in the field of online education. In this case, the implementation of complex instruction in online training courses for teachers, on "Social Networks in…

Cumulative complexity: a functional, patient-centered model of patient complexity can improve research and practice.

PubMed

Shippee, Nathan D; Shah, Nilay D; May, Carl R; Mair, Frances S; Montori, Victor M

2012-10-01

To design a functional, patient-centered model of patient complexity with practical applicability to analytic design and clinical practice. Existing literature on patient complexity has mainly identified its components descriptively and in isolation, lacking clarity as to their combined functions in disrupting care or to how complexity changes over time. The authors developed a cumulative complexity model, which integrates existing literature and emphasizes how clinical and social factors accumulate and interact to complicate patient care. A narrative literature review is used to explicate the model. The model emphasizes a core, patient-level mechanism whereby complicating factors impact care and outcomes: the balance between patient workload of demands and patient capacity to address demands. Workload encompasses the demands on the patient's time and energy, including demands of treatment, self-care, and life in general. Capacity concerns ability to handle work (e.g., functional morbidity, financial/social resources, literacy). Workload-capacity imbalances comprise the mechanism driving patient complexity. Treatment and illness burdens serve as feedback loops, linking negative outcomes to further imbalances, such that complexity may accumulate over time. With its components largely supported by existing literature, the model has implications for analytic design, clinical epidemiology, and clinical practice. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Social vulnerability from a social ecology perspective: a cohort study of older adults from the National Population Health Survey of Canada

PubMed Central

2014-01-01

Background Numerous social factors, generally studied in isolation, have been associated with older adults’ health. Even so, older people’s social circumstances are complex and an approach which embraces this complexity is desirable. Here we investigate many social factors in relation to one another and to survival among older adults using a social ecology perspective to measure social vulnerability among older adults. Methods 2740 adults aged 65 and older were followed for ten years in the Canadian National Population Health Survey (NPHS). Twenty-three individual-level social variables were drawn from the 1994 NPHS and five Enumeration Area (EA)-level variables were abstracted from the 1996 Canadian Census using postal code linkage. Principal Component Analysis (PCA) was used to identify dimensions of social vulnerability. All social variables were summed to create a social vulnerability index which was studied in relation to ten-year mortality. Results The PCA was limited by low variance (47%) explained by emergent factors. Seven dimensions of social vulnerability emerged in the most robust, yet limited, model: social support, engagement, living situation, self-esteem, sense of control, relations with others and contextual socio-economic status. These dimensions showed complex inter-relationships and were situated within a social ecology framework, considering spheres of influence from the individual through to group, neighbourhood and broader societal levels. Adjusting for age, sex, and frailty, increasing social vulnerability measured using the cumulative social vulnerability index was associated with increased risk of mortality over ten years in a Cox regression model (HR 1.04, 95% CI:1.01-1.07, p = 0.01). Conclusions Social vulnerability has important independent influence on older adults’ health though relationships between contributing variables are complex and do not lend themselves well to fragmentation into a small number of discrete factors. A social ecology perspective provides a candidate framework for further study of social vulnerability among older adults. PMID:25129548

Levels of Social Sharing and Clinical Implications for Severe Social Withdrawal in Patients with Personality Disorders.

PubMed

Colle, Livia; Pellecchia, Giovanni; Moroni, Fabio; Carcione, Antonino; Nicolò, Giuseppe; Semerari, Antonio; Procacci, Michele

2017-01-01

Social sharing capacities have attracted attention from a number of fields of social cognition and have been variously defined and analyzed in numerous studies. Social sharing consists in the subjective awareness that aspects of the self's experience are held in common with other individuals. The definition of social sharing must take a variety of elements into consideration: the motivational element, the contents of the social sharing experience, the emotional responses it evokes, the behavioral outcomes, and finally, the circumstances and the skills which enable social sharing. The primary objective of this study is to explore some of the diverse forms of human social sharing and to classify them according to levels of complexity. We identify four different types of social sharing, categorized according to the nature of the content being shared and the complexity of the mindreading skills required. The second objective of this study is to consider possible applications of this graded model of social sharing experience in clinical settings. Specifically, this model may support the development of graded, focused clinical interventions for patients with personality disorders characterized by severe social withdrawal.

Coordinating complex problem-solving among distributed intelligent agents

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1992-01-01

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

On some genetic consequences of social structure, mating systems, dispersal, and sampling

PubMed Central

Parreira, Bárbara R.; Chikhi, Lounès

2015-01-01

Many species are spatially and socially organized, with complex social organizations and dispersal patterns that are increasingly documented. Social species typically consist of small age-structured units, where a limited number of individuals monopolize reproduction and exhibit complex mating strategies. Here, we model social groups as age-structured units and investigate the genetic consequences of social structure under distinct mating strategies commonly found in mammals. Our results show that sociality maximizes genotypic diversity, which contradicts the belief that social groups are necessarily subject to strong genetic drift and at high risk of inbreeding depression. Social structure generates an excess of genotypic diversity. This is commonly observed in ecological studies but rarely reported in population genetic studies that ignore social structure. This heterozygosity excess, when detected, is often interpreted as a consequence of inbreeding avoidance mechanisms, but we show that it can occur even in the absence of such mechanisms. Many seemly contradictory results from ecology and population genetics can be reconciled by genetic models that include the complexities of social species. We find that such discrepancies can be explained by the intrinsic properties of social groups and by the sampling strategies of real populations. In particular, the number of social groups and the nature of the individuals that compose samples (e.g., nonreproductive and reproductive individuals) are key factors in generating outbreeding signatures. Sociality is an important component of population structure that needs to be revisited by ecologists and population geneticists alike. PMID:26080393

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.

Mathematical modelling of complex contagion on clustered networks

NASA Astrophysics Data System (ADS)

O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James

2015-09-01

The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.

A Model of Biological Attacks on a Realistic Population

NASA Astrophysics Data System (ADS)

Carley, Kathleen M.; Fridsma, Douglas; Casman, Elizabeth; Altman, Neal; Chen, Li-Chiou; Kaminsky, Boris; Nave, Demian; Yahja, Alex

The capability to assess the impacts of large-scale biological attacks and the efficacy of containment policies is critical and requires knowledge-intensive reasoning about social response and disease transmission within a complex social system. There is a close linkage among social networks, transportation networks, disease spread, and early detection. Spatial dimensions related to public gathering places such as hospitals, nursing homes, and restaurants, can play a major role in epidemics [Klovdahl et. al. 2001]. Like natural epidemics, bioterrorist attacks unfold within spatially defined, complex social systems, and the societal and networked response can have profound effects on their outcome. This paper focuses on bioterrorist attacks, but the model has been applied to emergent and familiar diseases as well.

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.

When high pressure, system constraints, and a social justice mission collide: A socio-structural analysis of emergency department social work services.

PubMed

Moore, Megan; Cristofalo, Margaret; Dotolo, Danae; Torres, Nicole; Lahdya, Alexandra; Ho, Leyna; Vogel, Mia; Forrester, Mollie; Conley, Bonnie; Fouts, Susan

2017-04-01

The emergency department (ED) can be a critical intervention point for many patients with multifaceted needs. Social workers have long been part of interdisciplinary ED teams. This study aimed to contribute to the limited understanding of social worker-patient interactions and factors influencing social work services in this setting. This paper reports a qualitative content analysis of social work medical record notes (N = 1509) of services provided to trauma patients in an urban, public, level 1 trauma center and an in-depth analysis of semi-structured interviews with ED social workers (N = 10). Eight major social work roles were identified: investigator, gatekeeper, resource broker, care coordinator, problem solver, crisis manager, advocate, discharge planner. Analyses revealed a complex interplay between ED social work services and multi-layered contexts. Using a social-ecological framework, we identified the interactions between micro or individual level factors, mezzo or local system level factors and macro environmental and systemic factors that play a role in ED interactions and patient services. Macro-level contextual influences were socio-structural forces including socioeconomic barriers to health, social hierarchies that reflected power differentials between providers and patients, and distrust or bias. Mezzo-level forces were limited resources, lack of healthcare system coordination, a challenging hierarchy within the medical model and the pressure to discharge patients quickly. Micro-level factors included characteristics of patients and social workers, complexity of patient stressors, empathic strain, lack of closure and compassion. All of these forces were at play in patient-social worker interactions and impacted service provision. Social workers were at times able to successfully navigate these forces, yet at other times these challenges were insurmountable. A conceptual model of ED social work and the influences on the patient-social worker interactions was developed to assist in guiding innovative research and practice models to improve services and outcomes in the complex, fast-paced ED. Copyright © 2017 Elsevier Ltd. All rights reserved.

When high pressure, system constraints, and a social justice mission collide: a socio-structural analysis of emergency department social work services

PubMed Central

Cristofalo, Margaret; Dotolo, Danae; Torres, Nicole; Lahdya, Alexandra; Ho, Leyna; Vogel, Mia; Forrester, Mollie; Conley, Bonnie; Fouts, Susan

2017-01-01

The emergency department (ED) can be a critical intervention point for many patients with multifaceted needs. Social workers have long been part of interdisciplinary ED teams. This study aimed to contribute to the limited understanding of social worker-patient interactions and factors influencing social work services in this setting. This paper reports a qualitative content analysis of social work medical record notes (N=1,509) of services provided to trauma patients in an urban, public, level 1 trauma center and an in-depth analysis of semi-structured interviews with ED social workers (N=10). Eight major social work roles were identified: investigator, gatekeeper, resource broker, care coordinator, problem solver, crisis manager, advocate, discharge planner. Analyses revealed a complex interplay between ED social work services and multi-layered contexts. Using a social-ecological framework, we identified the interactions between micro or individual level factors, mezzo or local system level factors and macro environmental and systemic factors that play a role in ED interactions and patient services. Macro-level contextual influences were socio-structural forces including socioeconomic barriers to health, social hierarchies that reflected power differentials between providers and patients, and distrust or bias. Mezzo-level forces were limited resources, lack of healthcare system coordination, a challenging hierarchy within the medical model and the pressure to discharge patients quickly. Micro-level factors included characteristics of patients and social workers, complexity of patient stressors, empathic strain, lack of closure and compassion. All of these forces were at play in patient-social worker interactions and impacted service provision. Social workers were at times able to successfully navigate these forces, yet at other times these challenges were insurmountable. A conceptual model of ED social work and the influences on the patient-social worker interactions was developed to assist in guiding innovative research and practice models to improve services and outcomes in the complex, fast-paced ED. PMID:28214722

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.

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…

Coevolution of landesque capital intensive agriculture and sociopolitical hierarchy

PubMed Central

Sheehan, Oliver; Gray, Russell D.; Atkinson, Quentin D.

2018-01-01

One of the defining trends of the Holocene has been the emergence of complex societies. Two essential features of complex societies are intensive resource use and sociopolitical hierarchy. Although it is widely agreed that these two phenomena are associated cross-culturally and have both contributed to the rise of complex societies, the causality underlying their relationship has been the subject of longstanding debate. Materialist theories of cultural evolution tend to view resource intensification as driving the development of hierarchy, but the reverse order of causation has also been advocated, along with a range of intermediate views. Phylogenetic methods have the potential to test between these different causal models. Here we report the results of a phylogenetic study that modeled the coevolution of one type of resource intensification—the development of landesque capital intensive agriculture—with political complexity and social stratification in a sample of 155 Austronesian-speaking societies. We found support for the coevolution of landesque capital with both political complexity and social stratification, but the contingent and nondeterministic nature of both of these relationships was clear. There was no indication that intensification was the “prime mover” in either relationship. Instead, the relationship between intensification and social stratification was broadly reciprocal, whereas political complexity was more of a driver than a result of intensification. These results challenge the materialist view and emphasize the importance of both material and social factors in the evolution of complex societies, as well as the complex and multifactorial nature of cultural evolution. PMID:29555760

Sociality influences cultural complexity.

PubMed

Muthukrishna, Michael; Shulman, Ben W; Vasilescu, Vlad; Henrich, Joseph

2014-01-07

Archaeological and ethnohistorical evidence suggests a link between a population's size and structure, and the diversity or sophistication of its toolkits or technologies. Addressing these patterns, several evolutionary models predict that both the size and social interconnectedness of populations can contribute to the complexity of its cultural repertoire. Some models also predict that a sudden loss of sociality or of population will result in subsequent losses of useful skills/technologies. Here, we test these predictions with two experiments that permit learners to access either one or five models (teachers). Experiment 1 demonstrates that naive participants who could observe five models, integrate this information and generate increasingly effective skills (using an image editing tool) over 10 laboratory generations, whereas those with access to only one model show no improvement. Experiment 2, which began with a generation of trained experts, shows how learners with access to only one model lose skills (in knot-tying) more rapidly than those with access to five models. In the final generation of both experiments, all participants with access to five models demonstrate superior skills to those with access to only one model. These results support theoretical predictions linking sociality to cumulative cultural evolution.

Sociality influences cultural complexity

PubMed Central

Muthukrishna, Michael; Shulman, Ben W.; Vasilescu, Vlad; Henrich, Joseph

2014-01-01

Archaeological and ethnohistorical evidence suggests a link between a population's size and structure, and the diversity or sophistication of its toolkits or technologies. Addressing these patterns, several evolutionary models predict that both the size and social interconnectedness of populations can contribute to the complexity of its cultural repertoire. Some models also predict that a sudden loss of sociality or of population will result in subsequent losses of useful skills/technologies. Here, we test these predictions with two experiments that permit learners to access either one or five models (teachers). Experiment 1 demonstrates that naive participants who could observe five models, integrate this information and generate increasingly effective skills (using an image editing tool) over 10 laboratory generations, whereas those with access to only one model show no improvement. Experiment 2, which began with a generation of trained experts, shows how learners with access to only one model lose skills (in knot-tying) more rapidly than those with access to five models. In the final generation of both experiments, all participants with access to five models demonstrate superior skills to those with access to only one model. These results support theoretical predictions linking sociality to cumulative cultural evolution. PMID:24225461

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.

A developmental approach to mentalizing communities: I. A model for social change.

PubMed

Twemlow, Stuart W; Fonagy, Peter; Sacco, Frank C

2005-01-01

A developmental model is proposed applying attachment theory to complex social systems to promote social change. The idea of mentalizing communities is outlined with a proposal for three projects testing the model: ways to reduce bullying and create a peaceful climate in schools, projects to promote compassion in cities by a focus of end-of-life care, and a mentalization-based intervention into parenting style of borderline and substance abusing parents.

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…

Exploring Pattern of Socialisation Conditions and Human Development by Nonlinear Multivariate Analysis.

ERIC Educational Resources Information Center

Grundmann, Matthias

Following the assumptions of ecological socialization research, adequate analysis of socialization conditions must take into account the multilevel and multivariate structure of social factors that impact on human development. This statement implies that complex models of family configurations or of socialization factors are needed to explain the…

Modelling the Evolution of Social Structure

PubMed Central

Sutcliffe, A. G.; Dunbar, R. I. M.; Wang, D.

2016-01-01

Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, ‘favour-the-few’ strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa. PMID:27427758

Levels of Social Sharing and Clinical Implications for Severe Social Withdrawal in Patients with Personality Disorders

PubMed Central

Colle, Livia; Pellecchia, Giovanni; Moroni, Fabio; Carcione, Antonino; Nicolò, Giuseppe; Semerari, Antonio; Procacci, Michele

2017-01-01

Social sharing capacities have attracted attention from a number of fields of social cognition and have been variously defined and analyzed in numerous studies. Social sharing consists in the subjective awareness that aspects of the self’s experience are held in common with other individuals. The definition of social sharing must take a variety of elements into consideration: the motivational element, the contents of the social sharing experience, the emotional responses it evokes, the behavioral outcomes, and finally, the circumstances and the skills which enable social sharing. The primary objective of this study is to explore some of the diverse forms of human social sharing and to classify them according to levels of complexity. We identify four different types of social sharing, categorized according to the nature of the content being shared and the complexity of the mindreading skills required. The second objective of this study is to consider possible applications of this graded model of social sharing experience in clinical settings. Specifically, this model may support the development of graded, focused clinical interventions for patients with personality disorders characterized by severe social withdrawal. PMID:29255430

Nonlinear model of epidemic spreading in a complex social network.

PubMed

Kosiński, Robert A; Grabowski, A

2007-10-01

The epidemic spreading in a human society is a complex process, which can be described on the basis of a nonlinear mathematical model. In such an approach the complex and hierarchical structure of social network (which has implications for the spreading of pathogens and can be treated as a complex network), can be taken into account. In our model each individual has one of the four permitted states: susceptible, infected, infective, unsusceptible or dead. This refers to the SEIR model used in epidemiology. The state of an individual changes in time, depending on the previous state and the interactions with other individuals. The description of the interpersonal contacts is based on the experimental observations of the social relations in the community. It includes spatial localization of the individuals and hierarchical structure of interpersonal interactions. Numerical simulations were performed for different types of epidemics, giving the progress of a spreading process and typical relationships (e.g. range of epidemic in time, the epidemic curve). The spreading process has a complex and spatially chaotic character. The time dependence of the number of infective individuals shows the nonlinear character of the spreading process. We investigate the influence of the preventive vaccinations on the spreading process. In particular, for a critical value of preventively vaccinated individuals the percolation threshold is observed and the epidemic is suppressed.

Integrating Social Activity Theory and Critical Discourse Analysis: A Multilayered Methodological Model for Examining Knowledge Mediation in Mentoring

ERIC Educational Resources Information Center

Becher, Ayelet; Orland-Barak, Lily

2016-01-01

This study suggests an integrative qualitative methodological framework for capturing complexity in mentoring activity. Specifically, the model examines how historical developments of a discipline direct mentors' mediation of professional knowledge through the language that they use. The model integrates social activity theory and a framework of…

Components of a Model for Forecasting Future Status of Selected Social Indicators. Department of Education Project on Social Indicators. Technical Report No. 3.

ERIC Educational Resources Information Center

Collazo, Andres; And Others

Since a great number of variables influence future educational outcomes, forecasting possible trends is a complex task. One such model, the cross-impact matrix, has been developed. The use of this matrix in forecasting future values of social indicators of educational outcomes is described. Variables associated with educational outcomes are used…

Complex adaptive systems: A new approach for understanding health practices.

PubMed

Gomersall, Tim

2018-06-22

This article explores the potential of complex adaptive systems theory to inform behaviour change research. A complex adaptive system describes a collection of heterogeneous agents interacting within a particular context, adapting to each other's actions. In practical terms, this implies that behaviour change is 1) socially and culturally situated; 2) highly sensitive to small baseline differences in individuals, groups, and intervention components; and 3) determined by multiple components interacting "chaotically". Two approaches to studying complex adaptive systems are briefly reviewed. Agent-based modelling is a computer simulation technique that allows researchers to investigate "what if" questions in a virtual environment. Applied qualitative research techniques, on the other hand, offer a way to examine what happens when an intervention is pursued in real-time, and to identify the sorts of rules and assumptions governing social action. Although these represent very different approaches to complexity, there may be scope for mixing these methods - for example, by grounding models in insights derived from qualitative fieldwork. Finally, I will argue that the concept of complex adaptive systems offers one opportunity to gain a deepened understanding of health-related practices, and to examine the social psychological processes that produce health-promoting or damaging actions.

A game theory-based trust measurement model for social networks.

PubMed

Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

2016-01-01

In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

Immersive Simulation of Complex Social Environments

DTIC Science & Technology

2008-12-01

Complexity, 7, 18–30. Dawkins , R., 1989: The Selfish Gene (2nd ed.). New York: Oxford University Press. Dennett, D. C., 1995: Darwin’s Dangerous...interpretation, bias, and misinformation, which create erroneous versions of what has transpired. Dawkins presents a model for describing knowledge...evolution within a social group through interpersonal exchange (memetics). ( Dawkins , 1987) Where genetic duplication tends to be precise (and mutation

Using Video Modeling to Teach Complex Social Sequences to Children with Autism

ERIC Educational Resources Information Center

Nikopoulos, Christos K.; Keenan, Mickey

2007-01-01

This study comprised of two experiments was designed to teach complex social sequences to children with autism. Experimental control was achieved by collecting data using means of within-system design methodology. Across a number of conditions children were taken to a room to view one of the four short videos of two people engaging in a simple…

The Dynamics of Coalition Formation on Complex Networks

NASA Astrophysics Data System (ADS)

Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

2015-08-01

Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

A Model of Factors Contributing to STEM Learning and Career Orientation

ERIC Educational Resources Information Center

Nugent, Gwen; Barker, Bradley; Welch, Greg; Grandgenett, Neal; Wu, ChaoRong; Nelson, Carl

2015-01-01

The purpose of this research was to develop and test a model of factors contributing to science, technology, engineering, and mathematics (STEM) learning and career orientation, examining the complex paths and relationships among social, motivational, and instructional factors underlying these outcomes for middle school youth. Social cognitive…

Predicting the behavior of techno-social systems.

PubMed

Vespignani, Alessandro

2009-07-24

We live in an increasingly interconnected world of techno-social systems, in which infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. Examples are provided by the Internet, the World Wide Web, WiFi communication technologies, and transportation and mobility infrastructures. The multiscale nature and complexity of these networks are crucial features in understanding and managing the networks. The accessibility of new data and the advances in the theory and modeling of complex networks are providing an integrated framework that brings us closer to achieving true predictive power of the behavior of techno-social systems.

Coevolution of landesque capital intensive agriculture and sociopolitical hierarchy.

PubMed

Sheehan, Oliver; Watts, Joseph; Gray, Russell D; Atkinson, Quentin D

2018-04-03

One of the defining trends of the Holocene has been the emergence of complex societies. Two essential features of complex societies are intensive resource use and sociopolitical hierarchy. Although it is widely agreed that these two phenomena are associated cross-culturally and have both contributed to the rise of complex societies, the causality underlying their relationship has been the subject of longstanding debate. Materialist theories of cultural evolution tend to view resource intensification as driving the development of hierarchy, but the reverse order of causation has also been advocated, along with a range of intermediate views. Phylogenetic methods have the potential to test between these different causal models. Here we report the results of a phylogenetic study that modeled the coevolution of one type of resource intensification-the development of landesque capital intensive agriculture-with political complexity and social stratification in a sample of 155 Austronesian-speaking societies. We found support for the coevolution of landesque capital with both political complexity and social stratification, but the contingent and nondeterministic nature of both of these relationships was clear. There was no indication that intensification was the "prime mover" in either relationship. Instead, the relationship between intensification and social stratification was broadly reciprocal, whereas political complexity was more of a driver than a result of intensification. These results challenge the materialist view and emphasize the importance of both material and social factors in the evolution of complex societies, as well as the complex and multifactorial nature of cultural evolution. Copyright © 2018 the Author(s). Published by PNAS.

Association of the Social Determinants of Health With Quality of Primary Care.

PubMed

Katz, Alan; Chateau, Dan; Enns, Jennifer E; Valdivia, Jeff; Taylor, Carole; Walld, Randy; McCulloch, Scott

2018-05-01

In primary care, there is increasing recognition of the difficulty of treating patients' immediate health concerns when their overall well-being is shaped by underlying social determinants of health. We assessed the association of social complexity factors with the quality of care patients received in primary care settings. Eleven social complexity factors were defined using administrative data on poverty, mental health, newcomer status, and justice system involvement from the Manitoba Population Research Data Repository. We measured the distribution of these factors among primary care patients who made at least 3 visits during 2010-2013 to clinicians in Manitoba, Canada. Using generalized linear mixed modeling, we measured 26 primary care indicators to compare the quality of care received by patients with 0 to 5 or more social complexity factors. Among 626,264 primary care patients, 54% were living with at least 1 social complexity factor, and 4% were living with 5 or more. Social complexity factors were strongly associated with poorer outcomes with respect to primary care indicators for prevention (eg, breast cancer screening; odds ratio [OR] = 0.77; 99% CI, 0.73-0.81), chronic disease management (eg, diabetes management; OR = 0.86; 99% CI, 0.79-0.92), geriatric care (eg, benzodiazepine prescriptions; OR = 1.63; 99% CI, 1.48-1.80), and use of health services (eg, ambulatory visits; OR = 1.09; 99% CI, 1.08-1.09). Linking health and social data demonstrates how social determinants are associated with primary care service provision. Our findings provide insight into the social needs of primary care populations, and may support the development of focused interventions to address social complexity in primary care. © 2018 Annals of Family Medicine, Inc.

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.

Dense power-law networks and simplicial complexes

NASA Astrophysics Data System (ADS)

Courtney, Owen T.; Bianconi, Ginestra

2018-05-01

There is increasing evidence that dense networks occur in on-line social networks, recommendation networks and in the brain. In addition to being dense, these networks are often also scale-free, i.e., their degree distributions follow P (k ) ∝k-γ with γ ∈(1 ,2 ] . Models of growing networks have been successfully employed to produce scale-free networks using preferential attachment, however these models can only produce sparse networks as the numbers of links and nodes being added at each time step is constant. Here we present a modeling framework which produces networks that are both dense and scale-free. The mechanism by which the networks grow in this model is based on the Pitman-Yor process. Variations on the model are able to produce undirected scale-free networks with exponent γ =2 or directed networks with power-law out-degree distribution with tunable exponent γ ∈(1 ,2 ) . We also extend the model to that of directed two-dimensional simplicial complexes. Simplicial complexes are generalization of networks that can encode the many body interactions between the parts of a complex system and as such are becoming increasingly popular to characterize different data sets ranging from social interacting systems to the brain. Our model produces dense directed simplicial complexes with power-law distribution of the generalized out-degrees of the nodes.

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.

Social network supported process recommender system.

PubMed

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

Group size and social conflict in complex societies.

PubMed

Shen, Sheng-Feng; Akçay, Erol; Rubenstein, Dustin R

2014-02-01

Conflicts of interest over resources or reproduction among individuals in a social group have long been considered to result in automatic and universal costs to group living. However, exploring how social conflict varies with group size has produced mixed empirical results. Here we develop a model that generates alternative predictions for how social conflict should vary with group size depending on the type of benefits gained from being in a social group. We show that a positive relationship between social conflict and group size is favored when groups form primarily for the benefits of sociality but not when groups form mainly for accessing group-defended resources. Thus, increased social conflict in animal societies should not be viewed as an automatic cost of larger social groups. Instead, studying the relationship between social conflict and the types of grouping benefits will be crucial for understanding the evolution of complex societies.

Corporate social responsibility: an assessment of the enlightened self-interest model.

PubMed

Keim, G D

1978-01-01

Much recent discussion of corporate social responsibility has concerned operationality. Many activities subsumed under corporate social responsibility can be shown to be public or partially public goods. The theory of public goods can clarify and explain some complex problems of operationalizing the social responsibility doctrine. An examination of philanthropy provides some behavioral applications.

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.

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

Seeing the System: Dynamics and Complexity of Technology Integration in Secondary Schools

ERIC Educational Resources Information Center

Howard, Sarah K.; Thompson, Kate

2016-01-01

This paper introduces system dynamics modeling to understand, visualize and explore technology integration in schools, through the development of a theoretical model of technology-related change in teachers' practice. Technology integration is a dynamic social practice, within the social system of education. It is difficult, if not nearly…

Predicting Human Preferences Using the Block Structure of Complex Social Networks

PubMed Central

Guimerà, Roger; Llorente, Alejandro; Moro, Esteban; Sales-Pardo, Marta

2012-01-01

With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point of view, as part of what has been called a “new” computational social science. Here, we propose a novel approach based on stochastic block models, which have been developed by sociologists as plausible models of complex networks of social interactions. Our model is in the spirit of predicting individuals' preferences based on the preferences of others but, rather than fitting a particular model, we rely on a Bayesian approach that samples over the ensemble of all possible models. We show that our approach is considerably more accurate than leading recommender algorithms, with major relative improvements between 38% and 99% over industry-level algorithms. Besides, our approach sheds light on decision-making processes by identifying groups of individuals that have consistently similar preferences, and enabling the analysis of the characteristics of those groups. PMID:22984533

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).

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

[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.

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.

Game Theory, Conditional Preferences, and Social Influence

PubMed Central

Stirling, Wynn C.; Felin, Teppo

2013-01-01

Neoclassical noncooperative game theory is based on a simple, yet powerful synthesis of mathematical and logical concepts: unconditional and immutable preference orderings and individual rationality. Although this structure has proven useful for characterizing competitive multi-player behavior, its applicability to scenarios involving complex social relationships is problematic. In this paper we directly address this limitation by the introduction of a conditional preference structure that permits players to modulate their preference orderings as functions of the preferences of other players. Embedding this expanded preference structure in a formal and graphical framework provides a systematic approach for characterizing a complex society. The result is an influence network that allows conditional preferences to propagate through the community, resulting in an emergent social model which characterizes all of the social relationships that exist and which leads to solution concepts that account for both group and individual interests. The Ultimatum game is presented as an example of how social influence can be modeled with conditional preferences. PMID:23451078

Game theory, conditional preferences, and social influence.

PubMed

Stirling, Wynn C; Felin, Teppo

2013-01-01

Neoclassical noncooperative game theory is based on a simple, yet powerful synthesis of mathematical and logical concepts: unconditional and immutable preference orderings and individual rationality. Although this structure has proven useful for characterizing competitive multi-player behavior, its applicability to scenarios involving complex social relationships is problematic. In this paper we directly address this limitation by the introduction of a conditional preference structure that permits players to modulate their preference orderings as functions of the preferences of other players. Embedding this expanded preference structure in a formal and graphical framework provides a systematic approach for characterizing a complex society. The result is an influence network that allows conditional preferences to propagate through the community, resulting in an emergent social model which characterizes all of the social relationships that exist and which leads to solution concepts that account for both group and individual interests. The Ultimatum game is presented as an example of how social influence can be modeled with conditional preferences.

Everyday value conflicts and integrative complexity of thought.

PubMed

Myyry, Liisa

2002-12-01

This study examined the value pluralism model in everyday value conflicts, and the effect of issue context on complexity of thought. According to the cognitive manager model we hypothesized that respondents would obtain a higher level of integrative complexity on personal issues that on professional and general issues. We also explored the relations of integrative complexity to value priorities, measured by the Schwartz Value Survey, and to emotional empathy. The value pluralism model was not supported by the data collected from 126 university students from social science, business and technology. The cognitive manager model was partially confirmed by data from females but not from males. Concerning value priorities, more complex respondents had higher regard for self-transcendence values, and less complex respondents for self-enhancement values Emotional empathy was also significantly related to complexity score.

A riot on campus: The effects of social identity complexity on emotions and reparative attitudes after ingroup-perpetrated violence.

PubMed

Costabile, Kristi A; Austin, Adrienne B

2018-01-01

When a group commits a transgression, members who identify closely with the group often engage in defensive strategies in which they are less likely to experience guilt and shame in response to the transgression than are less identified group members. Subsequently, highly identified group members are often less willing to offer reparations to the injured parties. Because appropriate emotional responses and reparations are critical to community reconciliation, the present investigation examined whether social identity complexity-the degree to which individuals perceive their multiple social identities as interrelated-reduced these defensive responses. In the aftermath of a campus riot, emotional responses and reparative attitudes of undergraduate students were assessed. Results indicated that individuals who closely identified with the university were in fact capable of experiencing guilt and shame, but only if they also had complex social identities. A path model indicated that emotional responses, in turn, predicted willingness to provide reparations to the campus community. Accordingly, social identity complexity provides a new approach to understanding responses to ingroup-perpetrated violence. © 2017 Wiley Periodicals, Inc.

An Associational Model for the Diffusion of Complex Innovations.

ERIC Educational Resources Information Center

Barnett, George A.

A paradigm for the study of the diffusion of complex innovations through a society is presented in this paper; the paradigm is useful for studying sociocultural change as innovations diffuse. The model is designed to account for change within social systems rather than in individuals, although it would also be consistent with information…

Evolution of Cooperation in Social Dilemmas on Complex Networks

PubMed Central

Iyer, Swami; Killingback, Timothy

2016-01-01

Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner’s dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games. PMID:26928428

Environmental Modeling

EPA Pesticide Factsheets

EPA's modeling community is working to gain insights into certain parts of a physical, biological, economic, or social system by conducting environmental assessments for Agency decision making to complex environmental issues.

Multilevel Model Prediction

ERIC Educational Resources Information Center

Frees, Edward W.; Kim, Jee-Seon

2006-01-01

Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling--model disturbances, random coefficients, and future response…

Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of R0

PubMed Central

Pellis, Lorenzo; Ball, Frank; Trapman, Pieter

2012-01-01

The basic reproduction number R0 is one of the most important quantities in epidemiology. However, for epidemic models with explicit social structure involving small mixing units such as households, its definition is not straightforward and a wealth of other threshold parameters has appeared in the literature. In this paper, we use branching processes to define R0, we apply this definition to models with households or other more complex social structures and we provide methods for calculating it. PMID:22085761

Social Network Supported Process Recommender System

PubMed Central

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced. PMID:24672309

Quantum-like Probabilistic Models Outside Physics

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

We present a quantum-like (QL) model in that contexts (complexes of e.g. mental, social, biological, economic or even political conditions) are represented by complex probability amplitudes. This approach gives the possibility to apply the mathematical quantum formalism to probabilities induced in any domain of science. In our model quantum randomness appears not as irreducible randomness (as it is commonly accepted in conventional quantum mechanics, e.g. by von Neumann and Dirac), but as a consequence of obtaining incomplete information about a system. We pay main attention to the QL description of processing of incomplete information. Our QL model can be useful in cognitive, social and political sciences as well as economics and artificial intelligence. In this paper we consider in a more detail one special application — QL modeling of brain's functioning. The brain is modeled as a QL-computer.

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.

The Common Factors Model: Implications for Transtheoretical Clinical Social Work Practice

ERIC Educational Resources Information Center

Cameron, Mark; Keenan, Elizabeth King

2010-01-01

Direct practice social workers today are challenged to address the requirements of the complex array of professional, organizational, institutional, and regulatory demands placed on them in the broader socioeconomic context of fewer resources and diminished public support for social welfare services in the United States. The common factors model…

Social Skills Assessment and Training for the Learning Disabled: Who's on First and What's on Second? Part II.

ERIC Educational Resources Information Center

Schumaker, Jean B.; Hazel, J. Stephen

1984-01-01

The authors review research on techniques to change social behavior, ranging from relatively simple manipulations of antecedent and consequent conditions to complex instructional "packages" involving didactic, modeling, rehearsal, and feedback procedures and examine issues involved in generalization of social skills training as well as ethical…

Forecasting Effects of Influence Operations: A Generative Social Science Methodology

DTIC Science & Technology

2012-03-22

that can be made in a turn (commAttempts). Two forms of this agent are used in this case study : a pamphlet distributor and an internet campaigner. The...model Echo (1995). Echo captures the behavior of complex adaptive systems by using a digital analogue to genetics. As agents replicate, “child...Sugarscape model demonstrated a new paradigm for the study of the social sciences using ABM, which they call generative social science (GSS). In

Modeling the origins of mammalian sociality: moderate evidence for matrilineal signatures in mouse lemur vocalizations.

PubMed

Kessler, Sharon E; Radespiel, Ute; Hasiniaina, Alida I F; Leliveld, Lisette M C; Nash, Leanne T; Zimmermann, Elke

2014-02-20

Maternal kin selection is a driving force in the evolution of mammalian social complexity and it requires that kin are distinctive from nonkin. The transition from the ancestral state of asociality to the derived state of complex social groups is thought to have occurred via solitary foraging, in which individuals forage alone, but, unlike the asocial ancestors, maintain dispersed social networks via scent-marks and vocalizations. We hypothesize that matrilineal signatures in vocalizations were an important part of these networks. We used the solitary foraging gray mouse lemur (Microcebus murinus) as a model for ancestral solitary foragers and tested for matrilineal signatures in their calls, thus investigating whether such signatures are already present in solitary foragers and could have facilitated the kin selection thought to have driven the evolution of increased social complexity in mammals. Because agonism can be very costly, selection for matrilineal signatures in agonistic calls should help reduce agonism between unfamiliar matrilineal kin. We conducted this study on a well-studied population of wild mouse lemurs at Ankarafantsika National Park, Madagascar. We determined pairwise relatedness using seven microsatellite loci, matrilineal relatedness by sequencing the mitrochondrial D-loop, and sleeping group associations using radio-telemetry. We recorded agonistic calls during controlled social encounters and conducted a multi-parametric acoustic analysis to determine the spectral and temporal structure of the agonistic calls. We measured 10 calls for each of 16 females from six different matrilineal kin groups. Calls were assigned to their matriline at a rate significantly higher than chance (pDFA: correct = 47.1%, chance = 26.7%, p = 0.03). There was a statistical trend for a negative correlation between acoustic distance and relatedness (Mantel Test: g = -1.61, Z = 4.61, r = -0.13, p = 0.058). Mouse lemur agonistic calls are moderately distinctive by matriline. Because sleeping groups consisted of close maternal kin, both genetics and social learning may have generated these acoustic signatures. As mouse lemurs are models for solitary foragers, we recommend further studies testing whether the lemurs use these calls to recognize kin. This would enable further modeling of how kin recognition in ancestral species could have shaped the evolution of complex sociality.

[Complexity of social and healthcare coordination in addictions and the role of the nurse].

PubMed

Molina Fernández, Antonio Jesús; González Riera, Javier; Montero Bancalero, Francisco José; Gómez-Salgado, Juan

2016-01-01

The present article discusses the psychosocial impact of basic and advanced concepts, such as social support and prevention, as well as to establish a link between theoretical models related to the social sphere on one side, and the health aspects on the other. This work is based on the context of the influence on health shared by community psychology and social psychology. Starting from the historical background of current approaches, a review is presented of those first actions focused on the care plan and they are framed in a reaction model to the drug problem, which progressed to the current healthcare network model, through the creation of Spanish National Action Plan on Drugs. The complexity of the problem is then broken down into the following key elements: Multifactorial Model of Drugs and Addictions, importance of prevention, and social support. Subsequently, a description is presented on the different levels of the healthcare network, with their different resources. This is also illustrated using a coordination protocol. Finally, it features the nursing approach to drugs, with its contributions, particularly as regards the coordination of resources, and aspects that must be developed for improvement in this area. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

PubMed

Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L

2017-04-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

USGS Publications Warehouse

Haak, Danielle M.; Fath, Brian D.; Forbes, Valery E.; Martin, Dustin R.; Pope, Kevin L.

2017-01-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensisalters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

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.

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.

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.

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.

Teaching Statistics--Despite Its Applications

ERIC Educational Resources Information Center

Ridgway, Jim; Nicholson, James; McCusker, Sean

2007-01-01

Evidence-based policy requires sophisticated modelling and reasoning about complex social data. The current UK statistics curricula do not equip tomorrow's citizens to understand such reasoning. We advocate radical curriculum reform, designed to require students to reason from complex data.

Interests diffusion on a semantic multiplex. Comparing Computer Science and American Physical Society communities

NASA Astrophysics Data System (ADS)

D'Agostino, Gregorio; De Nicola, Antonio

2016-10-01

Exploiting the information about members of a Social Network (SN) represents one of the most attractive and dwelling subjects for both academic and applied scientists. The community of Complexity Science and especially those researchers working on multiplex social systems are devoting increasing efforts to outline general laws, models, and theories, to the purpose of predicting emergent phenomena in SN's (e.g. success of a product). On the other side the semantic web community aims at engineering a new generation of advanced services tailored to specific people needs. This implies defining constructs, models and methods for handling the semantic layer of SNs. We combined models and techniques from both the former fields to provide a hybrid approach to understand a basic (yet complex) phenomenon: the propagation of individual interests along the social networks. Since information may move along different social networks, one should take into account a multiplex structure. Therefore we introduced the notion of "Semantic Multiplex". In this paper we analyse two different semantic social networks represented by authors publishing in the Computer Science and those in the American Physical Society Journals. The comparison allows to outline common and specific features.

Video Modeling and the Expression of Social Communication and Behavior Skills in Preschool and Elementary School Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Kutty, Seema

2012-01-01

Recent times have seen an increasing prevalence and incidence of children with ASD in school settings. Social, cognitive, and language process deficits directly impact the ability of children with ASD to effectively functioning within the complex social setting of schools. In particular, deficits are noted in the areas of social communication and…

The Genome and Methylome of a Beetle with Complex Social Behavior, Nicrophorus vespilloides (Coleoptera: Silphidae).

PubMed

Cunningham, Christopher B; Ji, Lexiang; Wiberg, R Axel W; Shelton, Jennifer; McKinney, Elizabeth C; Parker, Darren J; Meagher, Richard B; Benowitz, Kyle M; Roy-Zokan, Eileen M; Ritchie, Michael G; Brown, Susan J; Schmitz, Robert J; Moore, Allen J

2015-10-09

Testing for conserved and novel mechanisms underlying phenotypic evolution requires a diversity of genomes available for comparison spanning multiple independent lineages. For example, complex social behavior in insects has been investigated primarily with eusocial lineages, nearly all of which are Hymenoptera. If conserved genomic influences on sociality do exist, we need data from a wider range of taxa that also vary in their levels of sociality. Here, we present the assembled and annotated genome of the subsocial beetle Nicrophorus vespilloides, a species long used to investigate evolutionary questions of complex social behavior. We used this genome to address two questions. First, do aspects of life history, such as using a carcass to breed, predict overlap in gene models more strongly than phylogeny? We found that the overlap in gene models was similar between N. vespilloides and all other insect groups regardless of life history. Second, like other insects with highly developed social behavior but unlike other beetles, does N. vespilloides have DNA methylation? We found strong evidence for an active DNA methylation system. The distribution of methylation was similar to other insects with exons having the most methylated CpGs. Methylation status appears highly conserved; 85% of the methylated genes in N. vespilloides are also methylated in the hymentopteran Nasonia vitripennis. The addition of this genome adds a coleopteran resource to answer questions about the evolution and mechanistic basis of sociality and to address questions about the potential role of methylation in social behavior. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Segmented Assimilation Theory and the Life Model: An Integrated Approach to Understanding Immigrants and Their Children

ERIC Educational Resources Information Center

Piedra, Lissette M.; Engstrom, David W.

2009-01-01

The life model offers social workers a promising framework to use in assisting immigrant families. However, the complexities of adaptation to a new country may make it difficult for social workers to operate from a purely ecological approach. The authors use segmented assimilation theory to better account for the specificities of the immigrant…

A Parent-Child Interactional Model of Social Anxiety Disorder in Youth

ERIC Educational Resources Information Center

Ollendick, Thomas H.; Benoit, Kristy E.

2012-01-01

In this paper, one of the most common disorders of childhood and adolescence, social anxiety disorder (SAD), is examined to illustrate the complex and delicate interplay between parent and child factors that can result in normal development gone awry. Our parent-child model of SAD posits a host of variables that converge to occasion the onset and…

Intermittent dynamics in complex systems driven to depletion.

PubMed

Escobar, Juan V; Pérez Castillo, Isaac

2018-03-19

When complex systems are driven to depletion by some external factor, their non-stationary dynamics can present an intermittent behaviour between relative tranquility and burst of activity whose consequences are often catastrophic. To understand and ultimately be able to predict such dynamics, we propose an underlying mechanism based on sharp thresholds of a local generalized energy density that naturally leads to negative feedback. We find a transition from a continuous regime to an intermittent one, in which avalanches can be predicted despite the stochastic nature of the process. This model may have applications in many natural and social complex systems where a rapid depletion of resources or generalized energy drives the dynamics. In particular, we show how this model accurately describes the time evolution and avalanches present in a real social system.

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

PubMed Central

Hétu, Sébastien; Luo, Yi; D’Ardenne, Kimberlee; Lohrenz, Terry

2017-01-01

Abstract As models of shared expectations, social norms play an essential role in our societies. Since our social environment is changing constantly, our internal models of it also need to change. In humans, there is mounting evidence that neural structures such as the insula and the ventral striatum are involved in detecting norm violation and updating internal models. However, because of methodological challenges, little is known about the possible involvement of midbrain structures in detecting norm violation and updating internal models of our norms. Here, we used high-resolution cardiac-gated functional magnetic resonance imaging and a norm adaptation paradigm in healthy adults to investigate the role of the substantia nigra/ventral tegmental area (SN/VTA) complex in tracking signals related to norm violation that can be used to update internal norms. We show that the SN/VTA codes for the norm’s variance prediction error (PE) and norm PE with spatially distinct regions coding for negative and positive norm PE. These results point to a common role played by the SN/VTA complex in supporting both simple reward-based and social decision making. PMID:28981876

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).

[The economic-industrial health care complex and the social and economic dimension of development].

PubMed

Gadelha, Carlos Augusto Grabois; Costa, Laís Silveira; Maldonado, José

2012-12-01

The strategic role of health care in the national development agenda has been increasingly recognized and institutionalized. In addition to its importance as a structuring element of the Social Welfare State, health care plays a leading role in the generation of innovation - an essential element for competitiveness in knowledge society. However, health care's productive basis is still fragile, and this negatively affects both the universal provision of health care services and Brazil's competitive inclusion in the globalized environment. This situation suggests the need of a more systematic analysis of the complex relationships among productive, technological and social interests in the scope of health care. Consequently, it is necessary to produce further knowledge about the Economic-Industrial Health Care Complex due to its potential for contributing to a socially inclusive development model. This means reversing the hierarchy between economic and social interests in the sanitary field, thus minimizing the vulnerability of the Brazilian health care policy.

Working With Socially and Medically Complex Patients: When Care Transitions Are Circular, Overlapping, and Continual Rather Than Linear and Finite.

PubMed

Roberts, Shauna R; Crigler, Jane; Ramirez, Cristina; Sisco, Deborah; Early, Gerald L

2015-01-01

The care coordination program described here evolved from 5 years of trial and learning related to how to best serve our high-cost, high-utilizing, chronically ill, urban core patient population. In addition to medical complexity, they have daily challenges characteristic of persons served by Safety-Net health systems. Many have unstable health insurance status. Others have insecure housing. A number of patients have a history of substance use and mental illness. Many have fractured social supports. Although some of the best-known care transition models have been successful in reducing rehospitalizations and cost among patients studied, these models were developed for a relatively high functioning patient population with social support. We describe a successful approach targeted at working with patients who require a more intense and lengthy care coordination intervention to self-manage and reduce the cost of caring for their medical conditions. Using a diverse team and a set of replicable processes, we have demonstrated statistically significant reduction in the use of hospital and emergency services. Our intervention leverages the strengths and resilience of patients, focuses on trust and self-management, and targets heterogeneous "high-utilizer" patients with medical and social complexity.

Three Universities in Georgia, Kazakhstan and Kyrgyzstan: The Struggle against Corruption and for Social Cohesion

ERIC Educational Resources Information Center

Heyneman, Stephen P.

2007-01-01

Universities may contribute to a nation's social cohesion through both direct and indirect means. In their syllabi they may include techniques necessary for understanding complex social problems. Faculty may model good behaviour in terms of listening and understanding points of view that may contradict their own. University administrators may…

'Change of Heart!': A New E-Learning Model Geared to Addressing Complex and Sensitive Public Health Issues

ERIC Educational Resources Information Center

Hillier, Dawn; Mitchell, Alice; Millwood, Richard

2005-01-01

Psychosocial risk factors for poor health show that we are highly sensitive to particular dimensions of the social and work environments. Central is the contrast between mutually supportive collaborative relationships versus stressful relationships of social dominance--in the workplace and at home. These social ordeals can exacerbate the effect of…

An empirical assessment of driver motivation and emotional states in perceived safety margins under varied driving conditions.

PubMed

Zhang, Yu; Kaber, David B

2013-01-01

Motivation models in driving behaviour postulate that driver motives and emotional states dictate risk tolerance under various traffic conditions. The present study used time and driver performance-based payment systems to manipulate motivation and risk-taking behaviour. Ten participants drove to a predefined location in a simulated driving environment. Traffic patterns (density and velocity) were manipulated to cause driver behaviour adjustments due to the need to conform with the social norms of the roadway. The driving environment complexity was investigated as a mediating factor in risk tolerance. Results revealed the performance-based payment system to closely relate to risk-taking behaviour as compared with the time-based payment system. Drivers conformed with social norms associated with specific traffic patterns. Higher roadway complexity led to a more conservative safety margins and speeds. This research contributes to the further development of motivational models of driver behaviour. This study provides empirical justification for two motivation factors in driver risk-taking decisions, including compliance with social norm and emotions triggered by incentives. Environment complexity was identified as a mediating factor in motivational behaviour model. This study also recommended safety margin measures sensitive to changes in driver risk tolerance.

Cognitive risk factors explain the relations between neuroticism and social anxiety for males and females.

PubMed

Allan, Nicholas P; Oglesby, Mary E; Uhl, Aubree; Schmidt, Norman B

2017-04-01

The hierarchical model of vulnerabilities to emotional distress contextualizes the relation between neuroticism and social anxiety as occurring indirectly through cognitive risk factors. In particular, inhibitory intolerance of uncertainty (IU; difficulty in uncertain circumstances), fear of negative evaluation (FNE; fear of being judged negatively), and anxiety sensitivity (AS) social concerns (fear of outwardly observable anxiety) are related to social anxiety. It is unclear whether these risk factors uniquely relate to social anxiety, and whether they account for the relations between neuroticism and social anxiety. The indirect relations between neuroticism and social anxiety through these and other risk factors were examined using structural equation modeling in a sample of 462 individuals (M age = 36.56, SD = 12.93; 64.3% female). Results indicated that the relations between neuroticism and social anxiety could be explained through inhibitory IU, FNE, and AS social concerns. No gender differences were found. These findings provide support for the hierarchical model of vulnerabilities to emotional distress disorders, although the cognitive risk factors accounted for variance beyond their contribution to the relation between neuroticism and social anxiety, suggesting a more complex model than that expressed in the hierarchical model of vulnerabilities.

Quantifying social influence in an online cultural market.

PubMed

Krumme, Coco; Cebrian, Manuel; Pickard, Galen; Pentland, Sandy

2012-01-01

We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process--the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role.

Quantifying Social Influence in an Online Cultural Market

PubMed Central

Krumme, Coco; Cebrian, Manuel; Pickard, Galen; Pentland, Sandy

2012-01-01

We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process–the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role. PMID:22590493

The Curriculum Prerequisite Network: Modeling the Curriculum as a Complex System

ERIC Educational Resources Information Center

Aldrich, Preston R.

2015-01-01

This article advances the prerequisite network as a means to visualize the hidden structure in an academic curriculum. Networks have been used to represent a variety of complex systems ranging from social systems to biochemical pathways and protein interactions. Here, I treat the academic curriculum as a complex system with nodes representing…

Visual social network analysis: effective approach to model complex human social, behaviour & culture.

PubMed

Ahram, Tareq Z; Karwowski, Waldemar

2012-01-01

The advent and adoption of internet-based social networking has significantly altered our daily lives. The educational community has taken notice of the positive aspects of social networking such as creation of blogs and to support groups of system designers going through the same challenges and difficulties. This paper introduces a social networking framework for collaborative education, design and modeling of the next generation of smarter products and services. Human behaviour modeling in social networking application aims to ensure that human considerations for learners and designers have a prominent place in the integrated design and development of sustainable, smarter products throughout the total system lifecycle. Social networks blend self-directed learning and prescribed, existing information. The self-directed element creates interest within a learner and the ability to access existing information facilitates its transfer, and eventual retention of knowledge acquired.

The Teaching of Evidence-Based Practice in Social Work Higher Education--Living by the Charlie Parker Dictum: A Response to Papers by Shlonsky and Stern, and Soydan

ERIC Educational Resources Information Center

Springer, David W.

2007-01-01

This article, as a response to two papers, identifies five critical issues and themes related to the teaching of evidence-based practice (EBP) in social work higher education. These five themes are: defining EBP; modeling the complexity of EBP in teaching; examining social work curriculum; coordinating social work professional organizations; and…

Social learning modulates the lateralization of emotional valence.

PubMed

Shamay-Tsoory, Simone G; Lavidor, Michal; Aharon-Peretz, Judith

2008-08-01

Although neuropsychological studies of lateralization of emotion have emphasized valence (positive vs. negative) or type (basic vs. complex) dimensions, the interaction between the two dimensions has yet to be elucidated. The purpose of the current study was to test the hypothesis that recognition of basic emotions is processed preferentially by the right prefrontal cortex (PFC), whereas recognition of complex social emotions is processed preferentially by the left PFC. Experiment 1 assessed the ability of healthy controls and patients with right and left PFC lesions to recognize basic and complex emotions. Experiment 2 modeled the patient's data of Experiment 1 on healthy participants under lateralized displays of the emotional stimuli. Both experiments support the Type as well as the Valence Hypotheses. However, our findings indicate that the Valence Hypothesis holds for basic but less so for complex emotions. It is suggested that, since social learning overrules the basic preference of valence in the hemispheres, the processing of complex emotions in the hemispheres is less affected by valence.

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

Some considerations concerning the challenge of incorporating social variables into epidemiological models of infectious disease transmission.

PubMed

Barnett, Tony; Fournié, Guillaume; Gupta, Sunetra; Seeley, Janet

2015-01-01

Incorporation of 'social' variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection - a highly social process in human populations - may be considered with little reference to the social. The French sociologist Émile Durkheim proposed that the scientific study of society required identification and study of 'social currents'. Such 'currents' are what we might today describe as 'emergent properties', specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to represent complex social and economic processes bearing on infectious disease transmission.

Describing Ecosystem Complexity through Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

2011-12-01

Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

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.

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

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.

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

Acquisition of a socially learned tool use sequence in chimpanzees: Implications for cumulative culture

PubMed Central

Vale, Gillian L.; Davis, Sarah J.; Lambeth, Susan P.; Schapiro, Steven J.; Whiten, Andrew

2017-01-01

Cumulative culture underpins humanity’s enormous success as a species. Claims that other animals are incapable of cultural ratcheting are prevalent, but are founded on just a handful of empirical studies. Whether cumulative culture is unique to humans thus remains a controversial and understudied question that has far-reaching implications for our understanding of the evolution of this phenomenon. We investigated whether one of human’s two closest living primate relatives, chimpanzees, are capable of a degree of cultural ratcheting by exposing captive populations to a novel juice extraction task. We found that groups (N = 3) seeded with a model trained to perform a tool modification that built upon simpler, unmodified tool use developed the seeded tool method that allowed greater juice returns than achieved by groups not exposed to a trained model (non-seeded controls; N = 3). One non-seeded group also discovered the behavioral sequence, either by coupling asocial and social learning or by repeated invention. This behavioral sequence was found to be beyond what an additional control sample of chimpanzees (N = 1 group) could discover for themselves without a competent model and lacking experience with simpler, unmodified tool behaviors. Five chimpanzees tested individually with no social information, but with experience of simple unmodified tool use, invented part, but not all, of the behavioral sequence. Our findings indicate that (i) social learning facilitated the propagation of the model-demonstrated tool modification technique, (ii) experience with simple tool behaviors may facilitate individual discovery of more complex tool manipulations, and (iii) a subset of individuals were capable of learning relatively complex behaviors either by learning asocially and socially or by repeated invention over time. That chimpanzees learn increasingly complex behaviors through social and asocial learning suggests that humans’ extraordinary ability to do so was built on such prior foundations. PMID:29333058

The Social Process of Analyzing Real Water Resource Systems Plans and Management Policies

NASA Astrophysics Data System (ADS)

Loucks, Daniel

2016-04-01

Developing and applying systems analysis methods for improving the development and management of real world water resource systems, I have learned, is primarily a social process. This talk is a call for more recognition of this reality in the modeling approaches we propose in the papers and books we publish. The mathematical models designed to inform planners and managers of water systems that we see in many of our journals often seem more complex than they need be. They also often seem not as connected to reality as they could be. While it may be easier to publish descriptions of complex models than simpler ones, and while adding complexity to models might make them better able to mimic or resemble the actual complexity of the real physical and/or social systems or processes being analyzed, the usefulness of such models often can be an illusion. Sometimes the important features of reality that are of concern or interest to those who make decisions can be adequately captured using relatively simple models. Finding the right balance for the particular issues being addressed or the particular decisions that need to be made is an art. When applied to real world problems or issues in specific basins or regions, systems modeling projects often involve more attention to the social aspects than the mathematical ones. Mathematical models addressing connected interacting interdependent components of complex water systems are in fact some of the most useful methods we have to study and better understand the systems we manage around us. They can help us identify and evaluate possible alternative solutions to problems facing humanity today. The study of real world systems of interacting components using mathematical models is commonly called applied systems analyses. Performing such analyses with decision makers rather than of decision makers is critical if the needed trust between project personnel and their clients is to be developed. Using examples from recent and ongoing modeling projects in different parts of the world, this talk will attempt to show the dependency on the degree of project success with the degree of attention given to the communication between project personnel, the stakeholders and decision making institutions. It will also highlight how initial project terms-of-reference and expected outcomes can change, sometimes in surprising ways, during the course of such projects. Changing project objectives often result from changing stakeholder values, emphasizing the need for analyses that can adapt to this uncertainty.

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

The Social Work Role in Reducing 30-Day Readmissions: The Effectiveness of the Bridge Model of Transitional Care.

PubMed

Alvarez, Renae; Ginsburg, Jacob; Grabowski, Jessica; Post, Sharon; Rosenberg, Walter

2016-04-01

The hospital experience is taxing and confusing for patients and their families, particularly those with limited economic and social resources. This complexity often leads to disengagement, poor adherence to the plan of care, and high readmission rates. Novel approaches to addressing the complexities of transitional care are emerging as possible solutions. The Bridge Model is a person-centered, social work-led, interdisciplinary transitional care intervention that helps older adults safely transition from the hospital back to their homes and communities. The Bridge Model combines 3 key components-care coordination, case management, and patient engagement-which provide a seamless transition during this stressful time and improve the overall quality of transitional care for older adults, including reducing hospital readmissions. The post Affordable Care Act (ACA) and managed care environment's emphasis on value and quality support further development and expansion of transitional care strategies, such as the Bridge Model, which offer promising avenues to fulfil the triple aim by improving the quality of individual patient care while also impacting population health and controlling per capita costs.

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.

Partial Least Squares Structural Equation Modeling with R

ERIC Educational Resources Information Center

Ravand, Hamdollah; Baghaei, Purya

2016-01-01

Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…

Hidden multidimensional social structure modeling applied to biased social perception

NASA Astrophysics Data System (ADS)

Maletić, Slobodan; Zhao, Yi

2018-02-01

Intricacies of the structure of social relations are realized by representing a collection of overlapping opinions as a simplicial complex, thus building latent multidimensional structures, through which agents are, virtually, moving as they exchange opinions. The influence of opinion space structure on the distribution of opinions is demonstrated by modeling consensus phenomena when the opinion exchange between individuals may be affected by the false consensus effect. The results indicate that in the cases with and without bias, the road toward consensus is influenced by the structure of multidimensional space of opinions, and in the biased case, complete consensus is achieved. The applications of proposed modeling framework can easily be generalized, as they transcend opinion formation modeling.

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.

Segmented assimilation theory and the life model: an integrated approach to understanding immigrants and their children.

PubMed

Piedra, Lissette M; Engstrom, David W

2009-07-01

The life model offers social workers a promising framework to use in assisting immigrant families. However, the complexities of adaptation to a new country may make it difficult for social workers to operate from a purely ecological approach. The authors use segmented assimilation theory to better account for the specificities of the immigrant experience. They argue that by adding concepts from segmented assimilation theory to the life model, social workers can better understand the environmental stressors that increase the vulnerabilities of immigrants to the potentially harsh experience of adapting to a new country. With these concepts, social workers who work with immigrant families will be better positioned to achieve their central goal: enhancing person and environment fit.

An Individual-Oriented Model on the Emergence of Support in Fights, Its Reciprocation and Exchange

PubMed Central

Hemelrijk, Charlotte K.; Puga-Gonzalez, Ivan

2012-01-01

Complex social behaviour of primates has usually been attributed to the operation of complex cognition. Recently, models have shown that constraints imposed by the socio-spatial structuring of individuals in a group may result in an unexpectedly high number of patterns of complex social behaviour, resembling the dominance styles of egalitarian and despotic species of macaques and the differences between them. This includes affiliative patterns, such as reciprocation of grooming, grooming up the hierarchy, and reconciliation. In the present study, we show that the distribution of support in fights, which is the social behaviour that is potentially most sophisticated in terms of cognitive processes, may emerge in the same way. The model represents the spatial grouping of individuals and their social behaviour, such as their avoidance of risks during attacks, the self-reinforcing effects of winning and losing their fights, their tendency to join in fights of others that are close by (social facilitation), their tendency to groom when they are anxious, the reduction of their anxiety by grooming, and the increase of anxiety when involved in aggression. Further, we represent the difference in intensity of aggression apparent in egalitarian and despotic macaques. The model reproduces many aspects of support in fights, such as its different types, namely, conservative, bridging and revolutionary, patterns of choice of coalition partners attributed to triadic awareness, those of reciprocation of support and ‘spiteful acts’ and of exchange between support and grooming. This work is important because it suggests that behaviour that seems to result from sophisticated cognition may be a side-effect of spatial structure and dominance interactions and it shows that partial correlations fail to completely omit these effects of spatial structure. Further, the model is falsifiable, since it results in many patterns that can easily be tested in real primates by means of existing data. PMID:22666348

Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.

Triple Value Simulation Model Fact Sheet

EPA Pesticide Factsheets

The Triple Value Simulation (3VS) is a high-level model that accounts for the complex relationships among economic, social and environmental systems in order to explore scenarios and solutions to improve the health of the Bay.

Emotional valence and context of social influences on drug abuse-related behavior in animal models of social stress and prosocial interaction.

PubMed

Neisewander, J L; Peartree, N A; Pentkowski, N S

2012-11-01

Social factors are important determinants of drug dependence and relapse. We reviewed pre-clinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: (1) whether the social interaction is appetitive or aversive and (2) whether the social interaction occurs within or outside of the drug-taking context. The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors, whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse.

Nonequilibrium transitions in complex networks: A model of social interaction

NASA Astrophysics Data System (ADS)

Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; San Miguel, Maxi

2003-02-01

We analyze the nonequilibrium order-disorder transition of Axelrod’s model of social interaction in several complex networks. In a small-world network, we find a transition between an ordered homogeneous state and a disordered state. The transition point is shifted by the degree of spatial disorder of the underlying network, the network disorder favoring ordered configurations. In random scale-free networks the transition is only observed for finite size systems, showing system size scaling, while in the thermodynamic limit only ordered configurations are always obtained. Thus, in the thermodynamic limit the transition disappears. However, in structured scale-free networks, the phase transition between an ordered and a disordered phase is restored.

Entropy model of dissipative structure on corporate social responsibility

NASA Astrophysics Data System (ADS)

Li, Zuozhi; Jiang, Jie

2017-06-01

Enterprise is prompted to fulfill the social responsibility requirement by the internal and external environment. In this complex system, some studies suggest that firms have an orderly or chaotic entropy exchange behavior. Based on the theory of dissipative structure, this paper constructs the entropy index system of corporate social responsibility(CSR) and explores the dissipative structure of CSR through Brusselator model criterion. Picking up listed companies of the equipment manufacturing, the research shows that CSR has positive incentive to negative entropy and promotes the stability of dissipative structure. In short, the dissipative structure of CSR has a positive impact on the interests of stakeholders and corporate social images.

Emergence of social complexity among coastal hunter-gatherers in the Atacama Desert of northern Chile

PubMed Central

Marquet, Pablo A.; Santoro, Calogero M.; Latorre, Claudio; Standen, Vivien G.; Abades, Sebastián R.; Rivadeneira, Marcelo M.; Arriaza, Bernardo; Hochberg, Michael E.

2012-01-01

The emergence of complex cultural practices in simple hunter-gatherer groups poses interesting questions on what drives social complexity and what causes the emergence and disappearance of cultural innovations. Here we analyze the conditions that underlie the emergence of artificial mummification in the Chinchorro culture in the coastal Atacama Desert in northern Chile and southern Peru. We provide empirical and theoretical evidence that artificial mummification appeared during a period of increased coastal freshwater availability and marine productivity, which caused an increase in human population size and accelerated the emergence of cultural innovations, as predicted by recent models of cultural and technological evolution. Under a scenario of increasing population size and extreme aridity (with little or no decomposition of corpses) a simple demographic model shows that dead individuals may have become a significant part of the landscape, creating the conditions for the manipulation of the dead that led to the emergence of complex mortuary practices. PMID:22891345

How Family Status and Social Security Claiming Options Shape Optimal Life Cycle Portfolios

PubMed Central

Hubener, Andreas; Maurer, Raimond; Mitchell, Olivia S.

2017-01-01

We show how optimal household decisions regarding work, retirement, saving, portfolio allocations, and life insurance are shaped by the complex financial options embedded in U.S. Social Security rules and uncertain family transitions. Our life cycle model predicts sharp consumption drops on retirement, an age-62 peak in claiming rates, and earlier claiming by wives versus husbands and single women. Moreover, life insurance is mainly purchased on men’s lives. Our model, which takes Social Security rules seriously, generates wealth and retirement outcomes that are more consistent with the data, in contrast to earlier and less realistic models. PMID:28659659

"American" or "Multiethnic"? Family Ethnic Identity Among Transracial Adoptive Families, Ethnic-Racial Socialization, and Children's Self-Perception.

PubMed

Pinderhughes, Ellen E; Zhang, Xian; Agerbak, Susanne

2015-12-01

Drawing on a model of ethnic-racial socialization (E-RS; Pinderhughes, 2013), this study examined hypothesized relations among parents' role variables (family ethnic identity and acknowledgment of cultural and racial differences), cultural socialization (CS) behaviors, and children's self-perceptions (ethnic self-label and feelings about self-label). The sample comprised 44 U.S.-based parents and their daughters ages 6 to 9 who were adopted from China. Correlation analyses revealed that parents' role variables and CS behaviors were related, and children's ethnic self-label was related to family ethnic identity and CS behaviors. Qualitative analyses point to complexities in children's ethnic identity and between family and children's ethnic identities. Together, these findings provide support for the theoretical model and suggest that although ethnic identity among international transracial adoptees (ITRAs) has similarities to that of nonadopted ethnic minority children, their internal experiences are more complex. © 2015 Wiley Periodicals, Inc.

A development framework for artificial intelligence based distributed operations support systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1990-01-01

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

Causal inferences on the effectiveness of complex social programs: Navigating assumptions, sources of complexity and evaluation design challenges.

PubMed

Chatterji, Madhabi

2016-12-01

This paper explores avenues for navigating evaluation design challenges posed by complex social programs (CSPs) and their environments when conducting studies that call for generalizable, causal inferences on the intervention's effectiveness. A definition is provided of a CSP drawing on examples from different fields, and an evaluation case is analyzed in depth to derive seven (7) major sources of complexity that typify CSPs, threatening assumptions of textbook-recommended experimental designs for performing impact evaluations. Theoretically-supported, alternative methodological strategies are discussed to navigate assumptions and counter the design challenges posed by the complex configurations and ecology of CSPs. Specific recommendations include: sequential refinement of the evaluation design through systems thinking, systems-informed logic modeling; and use of extended term, mixed methods (ETMM) approaches with exploratory and confirmatory phases of the evaluation. In the proposed approach, logic models are refined through direct induction and interactions with stakeholders. To better guide assumption evaluation, question-framing, and selection of appropriate methodological strategies, a multiphase evaluation design is recommended. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Representation of People's Decisions in Health Information Systems. A Complementary Approach for Understanding Health Care Systems and Population Health.

PubMed

Gonzalez Bernaldo de Quiros, Fernan; Dawidowski, Adriana R; Figar, Silvana

2017-02-01

In this study, we aimed: 1) to conceptualize the theoretical challenges facing health information systems (HIS) to represent patients' decisions about health and medical treatments in everyday life; 2) to suggest approaches for modeling these processes. The conceptualization of the theoretical and methodological challenges was discussed in 2015 during a series of interdisciplinary meetings attended by health informatics staff, epidemiologists and health professionals working in quality management and primary and secondary prevention of chronic diseases of the Hospital Italiano de Buenos Aires, together with sociologists, anthropologists and e-health stakeholders. HIS are facing the need and challenge to represent social human processes based on constructivist and complexity theories, which are the current frameworks of human sciences for understanding human learning and socio-cultural changes. Computer systems based on these theories can model processes of social construction of concrete and subjective entities and the interrelationships between them. These theories could be implemented, among other ways, through the mapping of health assets, analysis of social impact through community trials and modeling of complexity with system simulation tools. This analysis suggested the need to complement the traditional linear causal explanations of disease onset (and treatments) that are the bases for models of analysis of HIS with constructivist and complexity frameworks. Both may enlighten the complex interrelationships among patients, health services and the health system. The aim of this strategy is to clarify people's decision making processes to improve the efficiency, quality and equity of the health services and the health system.

Transdisciplinarity and Translation: Preparing Social Work Doctoral Students for High Impact Research

ERIC Educational Resources Information Center

Nurius, Paula S.; Kemp, Susan P.

2014-01-01

Contemporary research models are becoming increasingly transdisciplinary (TD), multilevel, community-connected, and bent on expediting the movement of research to impact. This requires not only fresh thinking about the science of social work but an educational architecture that fosters both cross-disciplinary understanding of complex underlying…

Enhanced Perceptual Functioning in Autism: An Update, and Eight Principles of Autistic Perception

ERIC Educational Resources Information Center

Mottron, Laurent; Dawson, Michelle; Soulieres, Isabelle; Hubert, Benedicte; Burack, Jake

2006-01-01

We propose an "Enhanced Perceptual Functioning" model encompassing the main differences between autistic and non-autistic social and non-social perceptual processing: locally oriented visual and auditory perception, enhanced low-level discrimination, use of a more posterior network in "complex" visual tasks, enhanced perception…

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.

Interactive social contagions and co-infections on complex networks

NASA Astrophysics Data System (ADS)

Liu, Quan-Hui; Zhong, Lin-Feng; Wang, Wei; Zhou, Tao; Eugene Stanley, H.

2018-01-01

What we are learning about the ubiquitous interactions among multiple social contagion processes on complex networks challenges existing theoretical methods. We propose an interactive social behavior spreading model, in which two behaviors sequentially spread on a complex network, one following the other. Adopting the first behavior has either a synergistic or an inhibiting effect on the spread of the second behavior. We find that the inhibiting effect of the first behavior can cause the continuous phase transition of the second behavior spreading to become discontinuous. This discontinuous phase transition of the second behavior can also become a continuous one when the effect of adopting the first behavior becomes synergistic. This synergy allows the second behavior to be more easily adopted and enlarges the co-existence region of both behaviors. We establish an edge-based compartmental method, and our theoretical predictions match well with the simulation results. Our findings provide helpful insights into better understanding the spread of interactive social behavior in human society.

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.

A sampling model of social judgment.

PubMed

Galesic, Mirta; Olsson, Henrik; Rieskamp, Jörg

2018-04-01

Studies of social judgments have demonstrated a number of diverse phenomena that were so far difficult to explain within a single theoretical framework. Prominent examples are false consensus and false uniqueness, as well as self-enhancement and self-depreciation. Here we show that these seemingly complex phenomena can be a product of an interplay between basic cognitive processes and the structure of social and task environments. We propose and test a new process model of social judgment, the social sampling model (SSM), which provides a parsimonious quantitative account of different types of social judgments. In the SSM, judgments about characteristics of broader social environments are based on sampling of social instances from memory, where instances receive activation if they belong to a target reference class and have a particular characteristic. These sampling processes interact with the properties of social and task environments, including homophily, shapes of frequency distributions, and question formats. For example, in line with the model's predictions we found that whether false consensus or false uniqueness will occur depends on the level of homophily in people's social circles and on the way questions are asked. The model also explains some previously unaccounted-for patterns of self-enhancement and self-depreciation. People seem to be well informed about many characteristics of their immediate social circles, which in turn influence how they evaluate broader social environments and their position within them. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Paternal kin recognition in the high frequency / ultrasonic range in a solitary foraging mammal

PubMed Central

2012-01-01

Background Kin selection is a driving force in the evolution of mammalian social complexity. Recognition of paternal kin using vocalizations occurs in taxa with cohesive, complex social groups. This is the first investigation of paternal kin recognition via vocalizations in a small-brained, solitary foraging mammal, the grey mouse lemur (Microcebus murinus), a frequent model for ancestral primates. We analyzed the high frequency/ultrasonic male advertisement (courtship) call and alarm call. Results Multi-parametric analyses of the calls’ acoustic parameters and discriminant function analyses showed that advertisement calls, but not alarm calls, contain patrilineal signatures. Playback experiments controlling for familiarity showed that females paid more attention to advertisement calls from unrelated males than from their fathers. Reactions to alarm calls from unrelated males and fathers did not differ. Conclusions 1) Findings provide the first evidence of paternal kin recognition via vocalizations in a small-brained, solitarily foraging mammal. 2) High predation, small body size, and dispersed social systems may select for acoustic paternal kin recognition in the high frequency/ultrasonic ranges, thus limiting risks of inbreeding and eavesdropping by predators or conspecific competitors. 3) Paternal kin recognition via vocalizations in mammals is not dependent upon a large brain and high social complexity, but may already have been an integral part of the dispersed social networks from which more complex, kin-based sociality emerged. PMID:23198727

Neuropeptides and the social brain: potential rodent models of autism.

PubMed

Lim, Miranda M; Bielsky, Isadora F; Young, Larry J

2005-01-01

Conducting basic scientific research on a complex psychiatric disorder, such as autism, is a challenging prospect. It is difficult to dissociate the fundamental neurological and psychological processes that are disturbed in autism and, therefore, it is a challenge to discover accurate and reliable animal models of the disease. Because of their role in animal models of social processing and social bonding, the neuropeptides oxytocin and vasopressin are strong candidates for dysregulation in autism. In this review, we discuss the current animal models which have investigated oxytocin and vasopressin systems in the brain and their effects on social behavior. For example, mice lacking the oxytocin gene have profound deficits in social processing and social recognition, as do rats lacking vasopressin or mice lacking the vasopressin V1a receptor (V1aR). In another rodent model, monogamous prairie voles are highly social and form strong pair bonds with their mates. Pair bonds can be facilitated or disrupted by perturbing the oxytocin and vasopressin systems. Non-monogamous vole species that do not pair bond have different oxytocin and V1aR distribution patterns in the brain than monogamous vole species. Potential ties from these rodent models to the human autistic condition are then discussed. Given the hallmark disturbances in social function, the study of animal models of social behavior may provide novel therapeutic targets for the treatment of autism.

Social power and opinion formation in complex networks

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2013-02-01

In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts-Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given power to a random selection of nodes could not improve consensus properties. Introducing social power in Watts-Strogatz networks could not significantly change the consensus profile.

Intra-organizational Computation and Complexity

DTIC Science & Technology

2003-01-01

models. New methodologies, centered on understanding algorithmic complexity, are being developed that may enable us to better handle network data ...tractability of data analysis, and enable more precise theorization. A variety of measures of algorithmic complexity, e.g., Kolmogorov-Chaitin, and a...variety of proxies exist (which are often turned to for pragmatic reasons) ( Lempel and Ziv ,1976). For the most part, social and organizational

A study of the spreading scheme for viral marketing based on a complex network model

NASA Astrophysics Data System (ADS)

Yang, Jianmei; Yao, Canzhong; Ma, Weicheng; Chen, Guanrong

2010-02-01

Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.

Toward an Integrative Understanding of Social Behavior: New Models and New Opportunities

PubMed Central

Blumstein, Daniel T.; Ebensperger, Luis A.; Hayes, Loren D.; Vásquez, Rodrigo A.; Ahern, Todd H.; Burger, Joseph Robert; Dolezal, Adam G.; Dosmann, Andy; González-Mariscal, Gabriela; Harris, Breanna N.; Herrera, Emilio A.; Lacey, Eileen A.; Mateo, Jill; McGraw, Lisa A.; Olazábal, Daniel; Ramenofsky, Marilyn; Rubenstein, Dustin R.; Sakhai, Samuel A.; Saltzman, Wendy; Sainz-Borgo, Cristina; Soto-Gamboa, Mauricio; Stewart, Monica L.; Wey, Tina W.; Wingfield, John C.; Young, Larry J.

2010-01-01

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur. PMID:20661457

A Framework for Understanding and Generating Integrated Solutions for Residential Peak Energy Demand

PubMed Central

Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

2015-01-01

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times. PMID:25807384

A framework for understanding and generating integrated solutions for residential peak energy demand.

PubMed

Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

2015-01-01

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

Complex social contagion makes networks more vulnerable to disease outbreaks.

PubMed

Campbell, Ellsworth; Salathé, Marcel

2013-01-01

Social network analysis is now widely used to investigate the dynamics of infectious disease spread. Vaccination dramatically disrupts disease transmission on a contact network, and indeed, high vaccination rates can potentially halt disease transmission altogether. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread across social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model health behavior and infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This dynamic variability results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks.

Social molecular pathways and the evolution of bee societies

PubMed Central

Bloch, Guy; Grozinger, Christina M.

2011-01-01

Bees provide an excellent model with which to study the neuronal and molecular modifications associated with the evolution of sociality because relatively closely related species differ profoundly in social behaviour, from solitary to highly social. The recent development of powerful genomic tools and resources has set the stage for studying the social behaviour of bees in molecular terms. We review ‘ground plan’ and ‘genetic toolkit’ models which hypothesize that discrete pathways or sets of genes that regulate fundamental behavioural and physiological processes in solitary species have been co-opted to regulate complex social behaviours in social species. We further develop these models and propose that these conserved pathways and genes may be incorporated into ‘social pathways’, which consist of relatively independent modules involved in social signal detection, integration and processing within the nervous and endocrine systems, and subsequent behavioural outputs. Modifications within modules or in their connections result in the evolution of novel behavioural patterns. We describe how the evolution of pheromonal regulation of social pathways may lead to the expression of behaviour under new social contexts, and review plasticity in circadian rhythms as an example for a social pathway with a modular structure. PMID:21690132

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

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.

The oxytocin system in drug discovery for autism: Animal models and novel therapeutic strategies

PubMed Central

Modi, Meera E.; Young, Larry J.

2012-01-01

Animal models and behavioral paradigms are critical for elucidating the neural mechanism involved in complex behaviors, including social cognition. Both genotype and phenotype based models have implicated the neuropeptide oxytocin (OT) in the regulation of social behavior. Based on the findings in animal models, alteration of the OT system has been hypothesized to play a role in the social deficits associated with autism and other neuropsychiatric disorders. While the evidence linking the peptide to the etiology of the disorder is not yet conclusive, evidence from multiple animal models suggest modulation of the OT system may be a viable strategy for the pharmacological treatment of social deficits. In this review, we will discuss how animal models have been utilized to understand the role of OT in social cognition and how those findings can be applied to the conceptualization and treatment of the social impairments in ASD. Animal models with genetic alterations of the OT system, like the OT, OT receptor and CD38 knock-out mice, and those with phenotypic variation in social behavior, like BTBR inbred mice and prairie voles, coupled with behavioral paradigms with face and construct validity may prove to have predictive validity for identifying the most efficacious methods of stimulating the OT system to enhance social cognition in humans. The widespread use of strong animal models of social cognition has the potential yield pharmacological, interventions for the treatment social impairments psychiatric disorders. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior. PMID:22206823

Review of family relational stress and pediatric asthma: the value of biopsychosocial systemic models.

PubMed

Wood, Beatrice L; Miller, Bruce D; Lehman, Heather K

2015-06-01

Asthma is the most common chronic disease in children. Despite dramatic advances in pharmacological treatments, asthma remains a leading public health problem, especially in socially disadvantaged minority populations. Some experts believe that this health gap is due to the failure to address the impact of stress on the disease. Asthma is a complex disease that is influenced by multilevel factors, but the nature of these factors and their interrelations are not well understood. This paper aims to integrate social, psychological, and biological literatures on relations between family/parental stress and pediatric asthma, and to illustrate the utility of multilevel systemic models for guiding treatment and stimulating future research. We used electronic database searches and conducted an integrated analysis of selected epidemiological, longitudinal, and empirical studies. Evidence is substantial for the effects of family/parental stress on asthma mediated by both disease management and psychobiological stress pathways. However, integrative models containing specific pathways are scarce. We present two multilevel models, with supporting data, as potential prototypes for other such models. We conclude that these multilevel systems models may be of substantial heuristic value in organizing investigations of, and clinical approaches to, the complex social-biological aspects of family stress in pediatric asthma. However, additional systemic models are needed, and the models presented herein could serve as prototypes for model development. © 2015 Family Process Institute.

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.

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.

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…

Home range overlap as a driver of intelligence in primates.

PubMed

Grueter, Cyril C

2015-04-01

Various socioecological factors have been suggested to influence cognitive capacity in primates, including challenges associated with foraging and dealing with the complexities of social life. Alexander [Alexander, 1989]. Evolution of the human psyche. In: Mellars P, Stringer C, editors. The human revolution: Behavioural and biological perspectives on the origins of modern humans. Princeton: Princeton University Press. p 455-513] proposed an integrative model for the evolution of human cognitive abilities and complex sociality that incorporates competition among coalitions of conspecifics (inter-group conflict) as a major selective pressure. However, one of the premises of this model, i.e., that when confronted with inter-group conflict selection should favor enhanced cognition, has remained empirically untested. Using a comparative approach on species data, I aimed to test the prediction that primate species (n = 104) that face greater inter-group conflict have higher cognitive abilities (indexed by endocranial volume). The degree of inter-group conflict/complexity was approximated via the variable home range overlap among groups. I found a significant relationship between home range overlap and endocranial volume, even after controlling for other predictor variables and covariates such as group size and body mass. I conclude that brain size evolution cannot be attributed exclusively to social factors such as group size, but likely reflects a variety of social and ecological determinants including inter-group conflict which poses cognitive demands on monitoring both the wider social milieu as well as spatial attributes of the habitat. © 2014 Wiley Periodicals, Inc.

What can music tell us about social interaction?

PubMed

D'Ausilio, Alessandro; Novembre, Giacomo; Fadiga, Luciano; Keller, Peter E

2015-03-01

Humans are innately social creatures, but cognitive neuroscience, that has traditionally focused on individual brains, is only now beginning to investigate social cognition through realistic interpersonal interaction. Music provides an ideal domain for doing so because it offers a promising solution for balancing the trade-off between ecological validity and experimental control when testing cognitive and brain functions. Musical ensembles constitute a microcosm that provides a platform for parametrically modeling the complexity of human social interaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Childhood trauma and complex posttraumatic stress disorder symptoms in older adults: A study of direct effects and social-interpersonal factors as potential mediators.

PubMed

Krammer, Sandy; Kleim, Birgit; Simmen-Janevska, Keti; Maercker, Andreas

2016-01-01

Childhood traumatic events may lead to long-lasting psychological effects and contribute to the development of complex posttraumatic sequelae. These might be captured by the diagnostic concept of complex posttraumatic stress disorder (CPTSD) as an alternative to classic posttraumatic stress disorder (PTSD). CPTSD comprises a further set of symptoms in addition to those of PTSD, namely, changes in affect, self, and interpersonal relationships. Previous empirical research on CPTSD has focused on middle-aged adults but not on older adults. Moreover, predictor models of CPTSD are still rare. The current study investigated the association between traumatic events in childhood and complex posttraumatic stress symptoms in older adults. The mediation of this association by 2 social-interpersonal factors (social acknowledgment as a survivor and dysfunctional disclosure) was investigated. These 2 factors focus on the perception of acknowledgment by others and either the inability to disclose traumatic experiences or the ability to do so only with negative emotional reactions. A total of 116 older individuals (age range = 59-98 years) who had experienced childhood traumatic events completed standardized self-report questionnaires indexing childhood trauma, complex trauma sequelae, social acknowledgment, and dysfunctional disclosure of trauma. The results showed that traumatic events during childhood were associated with later posttraumatic stress symptoms but with classic rather than complex symptoms. Social acknowledgment and dysfunctional disclosure partially mediated this relationship. These findings suggest that childhood traumatic stress impacts individuals across the life span and may be associated with particular adverse psychopathological consequences.

Structural Equation Modeling of School Violence Data: Methodological Considerations

ERIC Educational Resources Information Center

Mayer, Matthew J.

2004-01-01

Methodological challenges associated with structural equation modeling (SEM) and structured means modeling (SMM) in research on school violence and related topics in the social and behavioral sciences are examined. Problems associated with multiyear implementations of large-scale surveys are discussed. Complex sample designs, part of any…

Emotional valence and context of social influences on drug abuse-related behavior in animal models of social stress and prosocial interaction

PubMed Central

Neisewander, J.L.; Peartree, N.A.; Pentkowski, N.S.

2014-01-01

Rationale Social factors are important determinants of drug dependence and relapse. Objectives We reviewed preclinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: 1) whether the social interaction is appetitive or aversive and 2) whether the social interaction occurs within or outside of the drug-taking context. Methods The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. Results We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Conclusions Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse. PMID:22955569

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

Social Interface Model: Theorizing Ecological Post-Delivery Processes for Intervention Effects.

PubMed

Pettigrew, Jonathan; Segrott, Jeremy; Ray, Colter D; Littlecott, Hannah

2018-01-03

Successful prevention programs depend on a complex interplay among aspects of the intervention, the participant, the specific intervention setting, and the broader set of contexts with which a participant interacts. There is a need to theorize what happens as participants bring intervention ideas and behaviors into other life-contexts, and theory has not yet specified how social interactions about interventions may influence outcomes. To address this gap, we use an ecological perspective to develop the social interface model. This paper presents the key components of the model and its potential to aid the design and implementation of prevention interventions. The model is predicated on the idea that intervention message effectiveness depends not only on message aspects but also on the participants' adoption and adaptation of the message vis-à-vis their social ecology. The model depicts processes by which intervention messages are received and enacted by participants through social processes occurring within and between relevant microsystems. Mesosystem interfaces (negligible interface, transference, co-dependence, and interdependence) can facilitate or detract from intervention effects. The social interface model advances prevention science by theorizing that practitioners can create better quality interventions by planning for what occurs after interventions are delivered.

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

ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

PubMed

González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

2014-03-24

This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

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.

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.

Social aggravation: Understanding the complex role of social relationships on stress and health-relevant physiology.

PubMed

Birmingham, Wendy C; Holt-Lunstad, Julianne

2018-04-05

There is a rich literature on social support and physical health, but research has focused primarily on the protective effects of social relationship. The stress buffering model asserts that relationships may be protective by being a source of support when coping with stress, thereby blunting health relevant physiological responses. Research also indicates relationships can be a source of stress, also influencing health. In other words, the social buffering influence may have a counterpart, a social aggravating influence that has an opposite or opposing effect. Drawing upon existing conceptual models, we expand these to delineate how social relationships may influence stress processes and ultimately health. This review summarizes the existing literature that points to the potential deleterious physiological effects of our relationships when they are sources of stress or exacerbate stress. Copyright © 2018 Elsevier B.V. All rights reserved.

Towards a social psychology-based microscopic model of driver behavior and decision-making : modifying Lewin's field theory

DOT National Transportation Integrated Search

2014-01-01

Central to effective roadway design is the ability to understand how drivers behave as they traverse a segment of : roadway. While simple and complex microscopic models have been used over the years to analyse driver behaviour, : most models: 1.) inc...

Evaluating an early intervention in psychosis service for 'high-risk' adolescents: symptomatic and social recovery outcomes.

PubMed

Lower, Rebecca; Wilson, Jonathan; Medin, Evelina; Corlett, Emma; Turner, Ruth; Wheeler, Karen; Fowler, David

2015-06-01

This study presents client characteristics and treatment outcomes for a group of young people seen by Central Norfolk Early Intervention Team (CNEIT). The team offers an intensive outreach model of treatment to young people with complex co-morbid emotional, behavioural and social problems, as well as the presence of psychotic symptoms. Outcomes include both client self-report and clinician-rated measures. Data are routinely collected at acceptance into service, after 12 months of service and at point of discharge. Data show that clients seen by the CNEIT youth team are a group of young people at high risk of developing long-term mental illness and social disability. Outcomes show significant reductions in not only psychotic symptomatology, but also co-morbid anxiety and depression, as well as improvements in social recovery. At the end of their time with the service, the majority of clients are discharged back to the care of their general practitioner, which indicates that the team successfully managed to reduce the complexity of needs and difficulties associated with this client group. Outcomes support the use of an intensive outreach approach for young people at high risk of developing psychotic disorders. It has been suggested that this model may be successfully broadened to young people with other emerging, potentially severe or complex mental disorders. Norfolk and Suffolk NHS Foundation Trust has built on the success of its youth early intervention team and innovatively redesigned its services in line with this model by developing a specific youth mental health service. © 2014 Wiley Publishing Asia Pty Ltd.

Differential lexical correlates of social cognition and metacognition in schizophrenia; a study of spontaneously-generated life narratives.

PubMed

Buck, Benjamin; Minor, Kyle S; Lysaker, Paul H

2015-04-01

Social cognition and metacognition have been identified as important cognitive domains in schizophrenia, which are separable from general neurocognition and predictive of functional and treatment outcomes. However, one challenge to improved models of schizophrenia has been the conceptual overlap between the two. One tool used in previous research to develop cognitive models of psychopathology is language analysis. In this article we aimed to clarify distinctions between social cognition and metacognition in schizophrenia using computerized language software. Fifty-eight (n=58) individuals with schizophrenia completed the Metacognitive Assessment Scale Abbreviated and measures of social cognition using the Hinting, Eyes, BLERT and Picture Arrangement test. A lexical analysis of participants' speech using Language Inquiry and Word Count software was conducted to examine relative frequencies of word types. Lexical characteristics were examined for their relationships to social cognition and metacognition. We found that lexical characteristics indicative of cognitive complexity were significantly related to level of metacognitive capacity while social cognition was related to second-person pronoun use, articles, and prepositions, and pronoun use overall. The relationships between lexical variables and metacognition persisted after controlling for demographics, verbal intelligence, and overall word count, but the same was not true for social cognition. Our findings provided support for the view that metacognition requires more synthetic and complex verbal and linguistic operations, while social cognition is associated with the representation and clear identification of others. Copyright © 2014 Elsevier Inc. All rights reserved.

Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence.

PubMed

Alshamsi, Aamena; Pianesi, Fabio; Lepri, Bruno; Pentland, Alex; Rahwan, Iyad

2015-01-01

Contagion, a concept from epidemiology, has long been used to characterize social influence on people's behavior and affective (emotional) states. While it has revealed many useful insights, it is not clear whether the contagion metaphor is sufficient to fully characterize the complex dynamics of psychological states in a social context. Using wearable sensors that capture daily face-to-face interaction, combined with three daily experience sampling surveys, we collected the most comprehensive data set of personality and emotion dynamics of an entire community of work. From this high-resolution data about actual (rather than self-reported) face-to-face interaction, a complex picture emerges where contagion (that can be seen as adaptation of behavioral responses to the behavior of other people) cannot fully capture the dynamics of transitory states. We found that social influence has two opposing effects on states: adaptation effects that go beyond mere contagion, and complementarity effects whereby individuals' behaviors tend to complement the behaviors of others. Surprisingly, these effects can exhibit completely different directions depending on the stable personality or emotional dispositions (stable traits) of target individuals. Our findings provide a foundation for richer models of social dynamics, and have implications on organizational engineering and workplace well-being.

Strong Start Wraparound: Addressing the Complex Needs of Mothers in Early Recovery

ERIC Educational Resources Information Center

Teel, M. Kay

2014-01-01

The Strong Start Study tested an innovative, High-Fidelity Wraparound intervention with families in early recovery from substance use. The Strong Start Wraparound model addressed the complex needs of pregnant and parenting women who were in early recovery to increase the protective factors of parental resilience, social connections, concrete…

Acute stress in adulthood impoverishes social choices and triggers aggressiveness in preclinical models.

PubMed

Nosjean, Anne; Cressant, Arnaud; de Chaumont, Fabrice; Olivo-Marin, Jean-Christophe; Chauveau, Frédéric; Granon, Sylvie

2014-01-01

Adult C57BL/6J mice are known to exhibit high level of social flexibility while mice lacking the β2 subunit of nicotinic receptors (β2(-/-) mice) present social rigidity. We asked ourselves what would be the consequences of a restraint acute stress (45 min) on social interactions in adult mice of both genotypes, hence the contribution of neuronal nicotinic receptors in this process. We therefore dissected social interaction complexity of stressed and not stressed dyads of mice in a social interaction task. We also measured plasma corticosterone levels in our experimental conditions. We showed that a single stress exposure occurring in adulthood reduced and disorganized social interaction complexity in both C57BL/6J and β2(-/-) mice. These stress-induced maladaptive social interactions involved alteration of distinct social categories and strategies in both genotypes, suggesting a dissociable impact of stress depending on the functioning of the cholinergic nicotinic system. In both genotypes, social behaviors under stress were coupled to aggressive reactions with no plasma corticosterone changes. Thus, aggressiveness appeared a general response independent of nicotinic function. We demonstrate here that a single stress exposure occurring in adulthood is sufficient to impoverish social interactions: stress impaired social flexibility in C57BL/6J mice whereas it reinforced β2(-/-) mice behavioral rigidity.

Military Social Work: Opportunities and Challenges for Social Work Education

PubMed Central

Wooten, Nikki R.

2015-01-01

Military social work is a specialized field of practice spanning the micro-macro continuum and requiring advanced social work knowledge and skills. The complex behavioral health problems and service needs of Iraq and Afghanistan veterans highlight the need for highly trained social work professionals who can provide militarily-relevant and culturally-responsive evidence-informed services. Responding to the military behavioral health workforce and service needs of recently returned veterans presents both opportunities and challenges for military social work education. This article discusses the rationale for a military social work specialization, the need for military social work education, and opportunities and challenges for social work education. An integrated model of intellectual capital is proposed to guide strategic planning for future military social work education. PMID:26089628

Emergent Societal Effects of Crimino-Social Forces in an Animat Agent Model

NASA Astrophysics Data System (ADS)

Scogings, Chris J.; Hawick, Ken A.

Societal behaviour can be studied at a causal level by perturbing a stable multi-agent model with new microscopic behaviours and observing the statistical response over an ensemble of simulated model systems. We report on the effects of introducing criminal and law-enforcing behaviours into a large scale animat agent model and describe the complex spatial agent patterns and population changes that result. Our well-established predator-prey substrate model provides a background framework against which these new microscopic behaviours can be trialled and investigated. We describe some quantitative results and some surprising conclusions concerning the overall societal health when individually anti-social behaviour is introduced.

Health behavior change models for HIV prevention and AIDS care: practical recommendations for a multi-level approach.

PubMed

Kaufman, Michelle R; Cornish, Flora; Zimmerman, Rick S; Johnson, Blair T

2014-08-15

Despite increasing recent emphasis on the social and structural determinants of HIV-related behavior, empirical research and interventions lag behind, partly because of the complexity of social-structural approaches. This article provides a comprehensive and practical review of the diverse literature on multi-level approaches to HIV-related behavior change in the interest of contributing to the ongoing shift to more holistic theory, research, and practice. It has the following specific aims: (1) to provide a comprehensive list of relevant variables/factors related to behavior change at all points on the individual-structural spectrum, (2) to map out and compare the characteristics of important recent multi-level models, (3) to reflect on the challenges of operating with such complex theoretical tools, and (4) to identify next steps and make actionable recommendations. Using a multi-level approach implies incorporating increasing numbers of variables and increasingly context-specific mechanisms, overall producing greater intricacies. We conclude with recommendations on how best to respond to this complexity, which include: using formative research and interdisciplinary collaboration to select the most appropriate levels and variables in a given context; measuring social and institutional variables at the appropriate level to ensure meaningful assessments of multiple levels are made; and conceptualizing intervention and research with reference to theoretical models and mechanisms to facilitate transferability, sustainability, and scalability.

How social factors and behavioural strategies affect feeding and social interaction patterns in pigs.

PubMed

Boumans, Iris J M M; de Boer, Imke J M; Hofstede, Gert Jan; Bokkers, Eddie A M

2018-04-26

Animals living in groups compete for food resources and face food conflicts. These conflicts are affected by social factors (e.g. competition level) and behavioural strategies (e.g. avoidance). This study aimed to deepen our understanding of the complex interactions between social factors and behavioural strategies affecting feeding and social interaction patterns in animals. We focused on group-housed growing pigs, Sus scrofa, which typically face conflicts around the feeder, and of which patterns in various competitive environments (i.e. pig:feeder ratio) have been documented soundly. An agent-based model was developed to explore how interactions among social factors and behavioural strategies can affect various feeding and social interaction patterns differently under competitive situations. Model results show that pig and diet characteristics interact with group size and affect daily feeding patterns (e.g. feed intake and feeding time) and conflicts around the feeder. The level of competition can cause a turning point in feeding and social interaction patterns. Beyond a certain point of competition, meal-based (e.g. meal frequency) and social interaction patterns (e.g. displacements) are determined mainly by behavioural strategies. The average daily feeding time can be used to predict the group size at which this turning point occurs. Under the model's assumptions, social facilitation was relatively unimportant in the causation of behavioural patterns in pigs. To validate our model, simulated patterns were compared with empirical patterns in conventionally housed pigs. Similarities between empirical and model patterns support the model results. Our model can be used as a tool in further research for studying the effects of social factors and group dynamics on individual variation in feeding and social interaction patterns in pigs, as well as in other animal species. Copyright © 2018 Elsevier Inc. All rights reserved.

Technology Acceptance Model for Wireless Internet.

ERIC Educational Resources Information Center

Lu, June; Yu, Chun-Sheng; Liu, Chang; Yao, James E.

2003-01-01

Develops a technology acceptance model (TAM) for wireless Internet via mobile devices (WIMD) and proposes that constructs, such as individual differences, technology complexity, facilitating conditions, social influences, and wireless trust environment determine user-perceived short and long-term usefulness, and ease of using WIMD. Twelve…

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

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.

Deconstructing Superorganisms and Societies to Address Big Questions in Biology.

PubMed

Kennedy, Patrick; Baron, Gemma; Qiu, Bitao; Freitak, Dalial; Helanterä, Heikki; Hunt, Edmund R; Manfredini, Fabio; O'Shea-Wheller, Thomas; Patalano, Solenn; Pull, Christopher D; Sasaki, Takao; Taylor, Daisy; Wyatt, Christopher D R; Sumner, Seirian

2017-11-01

Social insect societies are long-standing models for understanding social behaviour and evolution. Unlike other advanced biological societies (such as the multicellular body), the component parts of social insect societies can be easily deconstructed and manipulated. Recent methodological and theoretical innovations have exploited this trait to address an expanded range of biological questions. We illustrate the broadening range of biological insight coming from social insect biology with four examples. These new frontiers promote open-minded, interdisciplinary exploration of one of the richest and most complex of biological phenomena: sociality. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

A Grounded Theory of Sexual Minority Women and Transgender Individuals' Social Justice Activism.

PubMed

Hagen, Whitney B; Hoover, Stephanie M; Morrow, Susan L

2018-01-01

Psychosocial benefits of activism include increased empowerment, social connectedness, and resilience. Yet sexual minority women (SMW) and transgender individuals with multiple oppressed statuses and identities are especially prone to oppression-based experiences, even within minority activist communities. This study sought to develop an empirical model to explain the diverse meanings of social justice activism situated in SMW and transgender individuals' social identities, values, and experiences of oppression and privilege. Using a grounded theory design, 20 SMW and transgender individuals participated in initial, follow-up, and feedback interviews. The most frequent demographic identities were queer or bisexual, White, middle-class women with advanced degrees. The results indicated that social justice activism was intensely relational, replete with multiple benefits, yet rife with experiences of oppression from within and outside of activist communities. The empirically derived model shows the complexity of SMW and transgender individuals' experiences, meanings, and benefits of social justice activism.

Bayesian Analysis of Longitudinal Data Using Growth Curve Models

ERIC Educational Resources Information Center

Zhang, Zhiyong; Hamagami, Fumiaki; Wang, Lijuan Lijuan; Nesselroade, John R.; Grimm, Kevin J.

2007-01-01

Bayesian methods for analyzing longitudinal data in social and behavioral research are recommended for their ability to incorporate prior information in estimating simple and complex models. We first summarize the basics of Bayesian methods before presenting an empirical example in which we fit a latent basis growth curve model to achievement data…

Job Loss: An Individual Level Review and Model.

ERIC Educational Resources Information Center

DeFrank, Richard S.; Ivancevich, John M.

1986-01-01

Reviews behavioral, medical, and social science literature to illustrate the complexity and multidisciplinary nature of the job loss experience and provides a conceptual model to examine individual responses to job loss. Emphasizes the importance of including organizational-relevant variables in individual level conceptualizations and proposed…

Leadership, Social Capital and Coastal Community Resource Governance: the Case of the Destructive Seaweed Harvest in West Bali.

PubMed

Warren, Carol

This paper concerns resource governance in a remote Balinese coastal community, which faces severe environmental challenges due to overexploitation and habitat destruction. It explores some of the issues raised in 'social capital' debates regarding leadership and public participation toward sustainable natural resource governance. Given the strength of Balinese customary law and the high degree of participation required in the ritual-social domain, Bali represents a model context for examining these issues. Through a case study of destructive resource exploitation and evolving rules-in-use, this paper analyses the ambiguous role of 'bonding' social capital and the complexities of negotiating collective action on environmental problems where conflicting interests and dense social ties make local action difficult. The paper finds that a more complex appreciation of vertical (authority) and horizontal (solidarity) relationships between leaders and ordinary villagers is required, and that a more nuanced institutional bricolage and exploratory scenario approach to analysis of evolving rules in use would enhance associated policy interventions.

The recovery model and complex health needs: what health psychology can learn from mental health and substance misuse service provision.

PubMed

Webb, Lucy

2012-07-01

This article reviews key arguments around evidence-based practice and outlines the methodological demands for effective adoption of recovery model principles. The recovery model is outlined and demonstrated as compatible with current needs in substance misuse service provision. However, the concepts of evidence-based practice and the recovery model are currently incompatible unless the current value system of evidence-based practice changes to accommodate the methodologies demanded by the recovery model. It is suggested that critical health psychology has an important role to play in widening the scope of evidence-based practice to better accommodate complex social health needs.

Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach

PubMed Central

Senior, Alistair M.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

2016-01-01

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments. PMID:26858671

An emotional contagion model for heterogeneous social media with multiple behaviors

NASA Astrophysics Data System (ADS)

Xiong, Xi; Li, Yuanyuan; Qiao, Shaojie; Han, Nan; Wu, Yue; Peng, Jing; Li, Binyong

2018-01-01

The emotion varies and propagates with the spatial and temporal information of individuals through social media, which uncovers several interaction mechanisms and features the community structure in order to facilitate individuals' communication and emotional contagion in social networks. Aiming to show the detailed process and characteristics of emotional contagion within social media, we propose an emotional independent cascade model in which individual emotion can affect the subsequent emotion of his/her friends. The transmissibility is introduced to measure the capability of propagating emotion with respect to an individual in social networks. By analyzing the patterns of emotional contagion on Twitter data, we find that the value of transmissibility differs on different layers and on different community structures. Extensive experiments were conducted and the results reveal that, the polar emotion of hub users can lead to the disappearance of opposite emotion, and the transmissibility makes no sense. The final emotional distribution depends on the initial emotional distribution and the transmissibilities. Individuals from a small community are more likely to change their mood by the influence of community leaders. In addition, we compared the proposed model with two other models, the emotion-based spreader-ignorant-stifler model and the standard independent cascade model. The results demonstrate that the proposed model can reflect the real-world situation of emotional contagion for heterogeneous social media while the computational complexities of all these three models are similar.

Integrating Geomorphic and Social Dynamics in the Analysis of Anthropogenic Landforms: Examining Landscape Evolution of Terrain Modified by Agricultural Terracing

NASA Astrophysics Data System (ADS)

Glaubius, J.; Maerker, M.

2016-12-01

Anthropogenic landforms, such as mines and agricultural terraces, are impacted by both geomorphic and social processes at varying intensities through time. In the case of agricultural terraces, decisions regarding terrace maintenance are intertwined with land use, such as when terraced fields are abandoned. Furthermore, terrace maintenance and land use decisions, either jointly or separately, may be in response to geomorphic processes, as well as geomorphic feedbacks. Previous studies of these complex geomorphic systems considered agricultural terraces as static features or analyzed only the geomorphic response to landowner decisions. Such research is appropriate for short-term or binary landscape scenarios (e.g. the impact of maintained vs. abandoned terraces), but the complexities inherent in these socio-natural systems requires an approach that includes both social and geomorphic processes. This project analyzes feedbacks and emergent properties in terraced systems by implementing a coupled landscape evolution model (LEM) and agent-based model (ABM) using the Landlab and Mesa modeling libraries. In the ABM portion of the model, agricultural terraces are conceptualized using a life-cycle stages schema and implemented using Markov Decision Processes to simulate the changing geomorphic impact of terracing based on human decisions. This paper examines the applicability of this approach by comparing results from a LEM-only model against the coupled LEM-ABM model for a terraced region. Model results are compared by quantify and spatial patterning of sediment transport. This approach fully captures long-term landscape evolution of terraced terrain that is otherwise lost when the life-cycle of terraces is not considered. The coupled LEM-ABM approach balances both environmental and social processes so that the socio-natural feedbacks in such anthropogenic systems can be disentangled.

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…

Social Influence on Positive Youth Development: A Developmental Neuroscience Perspective.

PubMed

Telzer, Eva H; van Hoorn, Jorien; Rogers, Christina R; Do, Kathy T

2018-01-01

Susceptibility to social influence is associated with a host of negative outcomes during adolescence. However, emerging evidence implicates the role of peers and parents in adolescents' positive and adaptive adjustment. Hence, in this chapter we highlight social influence as an opportunity for promoting social adjustment, which can redirect negative trajectories and help adolescents thrive. We discuss influential models about the processes underlying social influence, with a particular emphasis on internalizing social norms, embedded in social learning and social identity theory. We link this behavioral work to developmental social neuroscience research, rooted in neurobiological models of decision making and social cognition. Work from this perspective suggests that the adolescent brain is highly malleable and particularly oriented toward the social world, which may account for heightened susceptibility to social influences during this developmental period. This chapter underscores the need to leverage social influences during adolescence, even beyond the family and peer context, to promote positive developmental outcomes. By further probing the underlying neural mechanisms as an additional layer to examining social influence on positive youth development, we will be able to gain traction on our understanding of this complex phenomenon. © 2018 Elsevier Inc. All rights reserved.

Marking Machinima: A Case Study in Assessing Student Use of a Web 2.0 Technology

ERIC Educational Resources Information Center

Barwell, Graham; Moore, Chris; Walker, Ruth

2011-01-01

The model of learning best suited to the future may be one which sees learning as the process of managing the different kinds of participation an individual might have in complex social systems. Learning capability and engagement is thus dependent on the relationship between an individual identity and social systems. We report on the incorporation…

An Empirical Investigation of Organizational Effectiveness and Performance.

DTIC Science & Technology

1983-07-29

on rerie side II necessaIr and Identify by block nuIb*’) Organizational Effectiveness Model of Effectiveness Corporate Strategy Organizational...complex and problematic task with little likelihood of reaching a final or even acceptable solution, social science research, never-the-less, should...regulations, interest rates, the weather, availability of supplies and raw materials, changing social values, and other external organizational events

The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators

PubMed Central

Karampourniotis, Panagiotis D.; Sreenivasan, Sameet; Szymanski, Boleslaw K.; Korniss, Gyorgy

2015-01-01

The threshold model is a simple but classic model of contagion spreading in complex social systems. To capture the complex nature of social influencing 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 accomplish this by employing a truncated normal distribution of the nodes’ thresholds and observe a non-monotonic change in the cascade size as we vary the standard deviation. Further, for a sufficiently large spread in the threshold distribution, the tipping-point behavior of the social influencing process disappears and is replaced by a smooth crossover governed by the size of initiator set. We demonstrate that for a given size of the initiator set, there is a specific variance of the threshold distribution for which an opinion spreads optimally. Furthermore, in the case of synthetic graphs we show that the spread asymptotically becomes independent of the system size, and that global cascades can arise just by the addition of a single node to the initiator set. PMID:26571486

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

Project EASE: a study to test a psychosocial model of epilepsy medication managment.

PubMed

DiIorio, Collen; Shafer, Patricia Osborne; Letz, Richard; Henry, Thomas R; Schomer, Donal L; Yeager, Kate

2004-12-01

The purpose of this study was to test a psychosocial model of medication self-management among people with epilepsy. This model was based primarily on social cognitive theory and included personal (self-efficacy, outcome expectations, goals, stigma, and depressive symptoms), social (social support), and provider (patient satisfaction and desire for control) variables. Participants for the study were enrolled at research sites in Atlanta, Georgia, and Boston, Massachusetts and completed computer-based assessments that included measures of the study variables listed above. The mean age of the 317 participants was 43.3 years; about 50% were female, and 81%white. Self-efficacy and patient satisfaction explained the most variance in medication management. Social support was related to self-efficacy; stigma to self-efficacy and depressive symptoms; and self-efficacy to outcome expectations and depressive symptoms. Findings reinforce that medication-taking behavior is affected by a complex set of interactions among psychosocial variables.

Exploring the Complex Pattern of Information Spreading in Online Blog Communities

PubMed Central

Pei, Sen; Muchnik, Lev; Tang, Shaoting; Zheng, Zhiming; Makse, Hernán A.

2015-01-01

Information spreading in online social communities has attracted tremendous attention due to its utmost practical values in applications. Despite that several individual-level diffusion data have been investigated, we still lack the detailed understanding of the spreading pattern of information. Here, by comparing information flows and social links in a blog community, we find that the diffusion processes are induced by three different spreading mechanisms: social spreading, self-promotion and broadcast. Although numerous previous studies have employed epidemic spreading models to simulate information diffusion, we observe that such models fail to reproduce the realistic diffusion pattern. In respect to users behaviors, strikingly, we find that most users would stick to one specific diffusion mechanism. Moreover, our observations indicate that the social spreading is not only crucial for the structure of diffusion trees, but also capable of inducing more subsequent individuals to acquire the information. Our findings suggest new directions for modeling of information diffusion in social systems, and could inform design of efficient propagation strategies based on users behaviors. PMID:25985081

Exploring the complex pattern of information spreading in online blog communities.

PubMed

Pei, Sen; Muchnik, Lev; Tang, Shaoting; Zheng, Zhiming; Makse, Hernán A

2015-01-01

Information spreading in online social communities has attracted tremendous attention due to its utmost practical values in applications. Despite that several individual-level diffusion data have been investigated, we still lack the detailed understanding of the spreading pattern of information. Here, by comparing information flows and social links in a blog community, we find that the diffusion processes are induced by three different spreading mechanisms: social spreading, self-promotion and broadcast. Although numerous previous studies have employed epidemic spreading models to simulate information diffusion, we observe that such models fail to reproduce the realistic diffusion pattern. In respect to users behaviors, strikingly, we find that most users would stick to one specific diffusion mechanism. Moreover, our observations indicate that the social spreading is not only crucial for the structure of diffusion trees, but also capable of inducing more subsequent individuals to acquire the information. Our findings suggest new directions for modeling of information diffusion in social systems, and could inform design of efficient propagation strategies based on users behaviors.

Effects of mass media action on the Axelrod model with social influence

NASA Astrophysics Data System (ADS)

Rodríguez, Arezky H.; Moreno, Y.

2010-07-01

The use of dyadic interaction between agents, in combination with homophily (the principle that “likes attract”) in the Axelrod model for the study of cultural dissemination, has two important problems: the prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with local convergence is obtained. Recently, the inclusion of social influence has proven to overcome them [A. Flache and M. W. Macy, e-print arXiv:0808.2710]. Here, we extend the Axelrod model with social influence interaction for the study of mass media effects through the inclusion of a superagent which acts over the whole system and has non-null overlap with each agent of the society. The dependence with different parameters as the initial social diversity, size effects, mass media strength, and noise is outlined. Our results might be relevant in several socioeconomic contexts and for the study of the emergence of collective behavior in complex social systems.

Effects of mass media action on the Axelrod model with social influence.

PubMed

Rodríguez, Arezky H; Moreno, Y

2010-07-01

The use of dyadic interaction between agents, in combination with homophily (the principle that "likes attract") in the Axelrod model for the study of cultural dissemination, has two important problems: the prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with local convergence is obtained. Recently, the inclusion of social influence has proven to overcome them [A. Flache and M. W. Macy, e-print arXiv:0808.2710]. Here, we extend the Axelrod model with social influence interaction for the study of mass media effects through the inclusion of a superagent which acts over the whole system and has non-null overlap with each agent of the society. The dependence with different parameters as the initial social diversity, size effects, mass media strength, and noise is outlined. Our results might be relevant in several socioeconomic contexts and for the study of the emergence of collective behavior in complex social systems.

Reducing racial disparities in obesity: simulating the effects of improved education and social network influence on diet behavior.

PubMed

Orr, Mark G; Galea, Sandro; Riddle, Matt; Kaplan, George A

2014-08-01

Understanding how to mitigate the present black-white obesity disparity in the United States is a complex issue, stemming from a multitude of intertwined causes. An appropriate but underused approach to guiding policy approaches to this problem is to account for this complexity using simulation modeling. We explored the efficacy of a policy that improved the quality of neighborhood schools in reducing racial disparities in obesity-related behavior and the dependence of this effect on social network influence and norms. We used an empirically grounded agent-based model to generate simulation experiments. We used a 2 × 2 × 2 factorial design that represented the presence or absence of improved neighborhood school quality, the presence or absence of social influence, and the type of social norm (healthy or unhealthy). Analyses focused on time trends in sociodemographic variables and diet quality. First, the quality of schools and social network influence had independent and interactive effects on diet behavior. Second, the black-white disparity in diet behavior was considerably reduced under some conditions, but never completely eliminated. Third, the degree to which the disparity in diet behavior was reduced was a function of the type of social norm that was in place; the reduction was the smallest when the type of social norm was healthy. Improving school quality can reduce, but not eliminate racial disparities in obesity-related behavior, and the degree to which this is true depends partly on social network effects. Copyright © 2014 Elsevier Inc. All rights reserved.

Social relationships and health: the relative roles of family functioning and social support.

PubMed

Franks, P; Campbell, T L; Shields, C G

1992-04-01

The associations between social relationships and health have been examined using two major research traditions. Using a social epidemiological approach, much research has shown the beneficial effect of social supports on health and health behaviors. Family interaction research, which has grown out of a more clinical tradition, has shown the complex effects of family functioning on health, particularly mental health. No studies have examined the relative power of these two approaches in explicating the connections between social relationships and health. We hypothesized that social relationships (social support and family functioning) would exert direct and indirect (through depressive symptoms) effects on health behaviors. We also hypothesized that the effects of social relationships on health would be more powerfully explicated by family functioning than by social support. We mailed a pilot survey to a random sample of patients attending a family practice center, including questions on depressive symptoms, cardiovascular health behaviors, demographics, social support using the ISEL scale, and family functioning using the FEICS scale. FEICS is a self-report questionnaire designed to assess family emotional involvement and criticism, the media elements of family expressed emotion. Eighty-three useable responses were obtained. Regression analyses and structural modelling showed both direct and indirect statistically significant paths from social relationships to health behaviors. Family criticism was directly associated (standardized coefficient = 0.29) with depressive symptoms, and family emotional involvement was directly associated with both depressive symptoms (coefficient = 0.35) and healthy cardiovascular behaviors (coefficient = 0.32). The results support the primacy of family functioning factors in understanding the associations among social relationships, mental health, and health behaviors. The contrasting relationships between emotional involvement and depressive symptoms on the one hand and emotional involvement and health behaviors on the other suggest the need for a more complex model to understand the connections between social relationships and health.

Bidirectional selection between two classes in complex social networks.

PubMed

Zhou, Bin; He, Zhe; Jiang, Luo-Luo; Wang, Nian-Xin; Wang, Bing-Hong

2014-12-19

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals' neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

Academic performance and perception of learning following a peer coaching teaching and assessment strategy.

PubMed

Moore, Catherine; Westwater-Wood, Sarah; Kerry, Roger

2016-03-01

Peer coaching has been associated with positive effects on learning. Specifically, these associations have been explored in complex healthcare professions. A social theory of learning has been proposed as a key component of the utility of peer coaching. Further, within the peer coaching model, assessment has been considered as an important driver. Empirical support for these dimensions of the model is lacking. To quantify assessment achievements and explore emergent attitudes and beliefs about learning related to a specific peer coaching model with integrated assessment. A longitudinal study based in a UK Higher Education Institute recorded assessment achievements and surveyed attitudes and beliefs in consecutive Year 1 undergraduate (physiotherapy) students (n = 560) between 2002 and 2012. A 6% improvement in academic achievement was demonstrated following the introduction of a peer coaching learning model. This was increased by a further 5% following the implementation of an integrated assessment. The improvement related to an overall averaged increase of one marking band. Students valued the strategy, and themes relating to the importance of social learning emerged from survey data. Peer coaching is an evidence-based teaching and learning strategy which can facilitate learning in complex subject areas. The strategy is underpinned by social learning theory which is supported by emergent student-reported attitudes.

Beyond prevalence to process: the role of self and identity in medical student well-being.

PubMed

Mavor, Kenneth I; McNeill, Kathleen G; Anderson, Katrina; Kerr, Annelise; O'Reilly, Erin; Platow, Michael J

2014-04-01

Problematic stress levels among medical students have been well established. This stress can lead to depression, suicidal ideation, substance abuse, burnout and cynicism, having a negative effect on students and their patients. We propose to move towards examining the processes underlying well-being in some medical students and vulnerability in others. We draw upon social psychological literature to propose that self-complexity, medical student identity and associated norms all have the capacity to influence medical students' well-being in both positive and negative ways. We identify two key dilemmas facing medical students with regard to the social psychological factors investigated. First, a diverse set of interests and a high level of self-complexity is thought to buffer against the effects of stress and might also be beneficial for medical practitioners, but the intensive nature of medical education makes it difficult for students to pursue outside interests, leading to a strongly focused identity. Second, a strong group identity is associated with high levels of social support and improved well-being, but unhealthy group norms may have a greater influence on individuals who have a strong group identity, encouraging them to engage in behaviours that place their well-being at risk. A model is proposed outlining how these potentially contradictory social psychological processes may combine to impact upon medical students' well-being. There is great scope for investigating the role of self-complexity, identity and norms in the medical education context, with room to investigate each of these factors alone and in combination. We highlight how our proposed model can inform medical educators as to the students who may be most vulnerable to the effects of stress and the potential interventions from which they may benefit. We conclude that social psychological factors make a valuable contribution to understanding the complex issue of well-being in medical education. © 2014 John Wiley & Sons Ltd.

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

PubMed Central

Wu, Jun; Su, Zhou; Li, Jianhua

2017-01-01

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. PMID:28758943

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems.

PubMed

Wu, Jun; Su, Zhou; Wang, Shen; Li, Jianhua

2017-07-30

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

Acute stress in adulthood impoverishes social choices and triggers aggressiveness in preclinical models

PubMed Central

Nosjean, Anne; Cressant, Arnaud; de Chaumont, Fabrice; Olivo-Marin, Jean-Christophe; Chauveau, Frédéric; Granon, Sylvie

2015-01-01

Adult C57BL/6J mice are known to exhibit high level of social flexibility while mice lacking the β2 subunit of nicotinic receptors (β2−/− mice) present social rigidity. We asked ourselves what would be the consequences of a restraint acute stress (45 min) on social interactions in adult mice of both genotypes, hence the contribution of neuronal nicotinic receptors in this process. We therefore dissected social interaction complexity of stressed and not stressed dyads of mice in a social interaction task. We also measured plasma corticosterone levels in our experimental conditions. We showed that a single stress exposure occurring in adulthood reduced and disorganized social interaction complexity in both C57BL/6J and β2−/− mice. These stress-induced maladaptive social interactions involved alteration of distinct social categories and strategies in both genotypes, suggesting a dissociable impact of stress depending on the functioning of the cholinergic nicotinic system. In both genotypes, social behaviors under stress were coupled to aggressive reactions with no plasma corticosterone changes. Thus, aggressiveness appeared a general response independent of nicotinic function. We demonstrate here that a single stress exposure occurring in adulthood is sufficient to impoverish social interactions: stress impaired social flexibility in C57BL/6J mice whereas it reinforced β2−/− mice behavioral rigidity. PMID:25610381

Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models

PubMed Central

Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

2015-01-01

Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development. PMID:26483621

Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models.

PubMed

Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

2015-01-01

Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development.

An arms race between producers and scroungers can drive the evolution of social cognition

PubMed Central

2014-01-01

The “social intelligence hypothesis” states that the need to cope with complexities of social life has driven the evolution of advanced cognitive abilities. It is usually invoked in the context of challenges arising from complex intragroup structures, hierarchies, and alliances. However, a fundamental aspect of group living remains largely unexplored as a driving force in cognitive evolution: the competition between individuals searching for resources (producers) and conspecifics that parasitize their findings (scroungers). In populations of social foragers, abilities that enable scroungers to steal by outsmarting producers, and those allowing producers to prevent theft by outsmarting scroungers, are likely to be beneficial and may fuel a cognitive arms race. Using analytical theory and agent-based simulations, we present a general model for such a race that is driven by the producer–scrounger game and show that the race’s plausibility is dramatically affected by the nature of the evolving abilities. If scrounging and scrounging avoidance rely on separate, strategy-specific cognitive abilities, arms races are short-lived and have a limited effect on cognition. However, general cognitive abilities that facilitate both scrounging and scrounging avoidance undergo stable, long-lasting arms races. Thus, ubiquitous foraging interactions may lead to the evolution of general cognitive abilities in social animals, without the requirement of complex intragroup structures. PMID:24822021

Transdisciplinary application of the cross-scale resilience model

USGS Publications Warehouse

Sundstrom, Shana M.; Angeler, David G.; Garmestani, Ahjond S.; Garcia, Jorge H.; Allen, Craig R.

2014-01-01

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 underlying discontinuity 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.

Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

PubMed

Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle

2016-02-01

This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

Social cognition in anorexia nervosa: Specific difficulties in decoding emotional but not nonemotional mental states.

PubMed

Brockmeyer, Timo; Pellegrino, Judith; Münch, Hannah; Herzog, Wolfgang; Dziobek, Isabell; Friederich, Hans-Christoph

2016-09-01

Building on recent models of anorexia nervosa (AN) that emphasize the importance of impaired social cognition in the development and maintenance of the disorder, the present study aimed at examining whether women with AN have more difficulties with inferring other people's emotional and nonemotional mental states than healthy women. Social cognition was assessed in 25 adult women with AN and 25 age-matched healthy women. To overcome limitations of previous research on social cognition in AN, the processing of social information was examined in a more complex and ecologically valid manner. The Movie for the Assessment of Social Cognition (MASC) reflects complex real-life social interaction and allows for disentangling emotional and non-emotional mental state inference as well as different types of errors in mentalizing. Women with AN showed poorer emotional mental state inference, whereas non-emotional mental state inference was largely intact. Groups did not differ in undermentalizing (overly simplistic theory of mind) and overmentalizing (overly complex or over-interpretative mental state reasoning). Performance in the MASC was independent of levels of eating disorder psychopathology and symptoms of depression and anxiety. The findings suggest that AN is associated with specific difficulties in emotional mental state inference despite largely intact nonemotional mental state inference. Upon replication in larger samples, these findings advocate a stronger emphasis on socio-emotional processing in AN treatment. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2016; 49:883-890). © 2016 Wiley Periodicals, Inc.

A Two-Stage Approach to Synthesizing Covariance Matrices in Meta-Analytic Structural Equation Modeling

ERIC Educational Resources Information Center

Cheung, Mike W. L.; Chan, Wai

2009-01-01

Structural equation modeling (SEM) is widely used as a statistical framework to test complex models in behavioral and social sciences. When the number of publications increases, there is a need to systematically synthesize them. Methodology of synthesizing findings in the context of SEM is known as meta-analytic SEM (MASEM). Although correlation…

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...

An Improved Estimation Using Polya-Gamma Augmentation for Bayesian Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S.

2018-01-01

Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…

Understanding, creating, and managing complex techno-socio-economic systems: Challenges and perspectives

NASA Astrophysics Data System (ADS)

Helbing, D.; Balietti, S.; Bishop, S.; Lukowicz, P.

2011-05-01

This contribution reflects on the comments of Peter Allen [1], Bikas K. Chakrabarti [2], Péter Érdi [3], Juval Portugali [4], Sorin Solomon [5], and Stefan Thurner [6] on three White Papers (WP) of the EU Support Action Visioneer (www.visioneer.ethz.ch). These White Papers are entitled "From Social Data Mining to Forecasting Socio-Economic Crises" (WP 1) [7], "From Social Simulation to Integrative System Design" (WP 2) [8], and "How to Create an Innovation Accelerator" (WP 3) [9]. In our reflections, the need and feasibility of a "Knowledge Accelerator" is further substantiated by fundamental considerations and recent events around the globe. newpara The Visioneer White Papers propose research to be carried out that will improve our understanding of complex techno-socio-economic systems and their interaction with the environment. Thereby, they aim to stimulate multi-disciplinary collaborations between ICT, the social sciences, and complexity science. Moreover, they suggest combining the potential of massive real-time data, theoretical models, large-scale computer simulations and participatory online platforms. By doing so, it would become possible to explore various futures and to expand the limits of human imagination when it comes to the assessment of the often counter-intuitive behavior of these complex techno-socio-economic-environmental systems. In this contribution, we also highlight the importance of a pluralistic modeling approach and, in particular, the need for a fruitful interaction between quantitative and qualitative research approaches. newpara In an appendix we briefly summarize the concept of the FuturICT flagship project, which will build on and go beyond the proposals made by the Visioneer White Papers. EU flagships are ambitious multi-disciplinary high-risk projects with a duration of at least 10 years amounting to an envisaged overall budget of 1 billion EUR [10]. The goal of the FuturICT flagship initiative is to understand and manage complex, global, socially interactive systems, with a focus on sustainability and resilience.

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

Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.

PubMed

Peng, Huan-Kai; Marculescu, Radu

2015-01-01

Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different time scales, and (2) the way in which these signatures interact and form higher-level meanings. In this paper, we propose the Recursive Convolutional Bayesian Model (RCBM) to address both of these fundamental questions. The key idea behind our approach consists of constructing a deep-learning framework using specialized convolution operators that are designed to exploit the inherent heterogeneity of social dynamics. RCBM's runtime and convergence properties are guaranteed by formal analyses. Experimental results show that the proposed method outperforms the state-of-the-art approaches both in terms of solution quality and computational efficiency. Indeed, by applying the proposed method on two social network datasets, Twitter and Yelp, we are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. Finally, our analysis offers new insights on understanding and engineering social media dynamics, with direct applications to opinion spreading and online content promotion.

Linear units improve articulation between social and physical constructs: An example from caregiver parameterization for children supported by complex medical technologies

NASA Astrophysics Data System (ADS)

Bezruczko, N.; Stanley, T.; Battle, M.; Latty, C.

2016-11-01

Despite broad sweeping pronouncements by international research organizations that social sciences are being integrated into global research programs, little attention has been directed toward obstacles blocking productive collaborations. In particular, social sciences routinely implement nonlinear, ordinal measures, which fundamentally inhibit integration with overarching scientific paradigms. The widely promoted general linear model in contemporary social science methods is largely based on untransformed scores and ratings, which are neither objective nor linear. This issue has historically separated physical and social sciences, which this report now asserts is unnecessary. In this research, nonlinear, subjective caregiver ratings of confidence to care for children supported by complex, medical technologies were transformed to an objective scale defined by logits (N=70). Transparent linear units from this transformation provided foundational insights into measurement properties of a social- humanistic caregiving construct, which clarified physical and social caregiver implications. Parameterized items and ratings were also subjected to multivariate hierarchical analysis, then decomposed to demonstrate theoretical coherence (R2 >.50), which provided further support for convergence of mathematical parameterization, physical expectations, and a social-humanistic construct. These results present substantial support for improving integration of social sciences with contemporary scientific research programs by emphasizing construction of common variables with objective, linear units.

Multi-Scale Compositionality: Identifying the Compositional Structures of Social Dynamics Using Deep Learning

PubMed Central

Peng, Huan-Kai; Marculescu, Radu

2015-01-01

Objective Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different time scales, and (2) the way in which these signatures interact and form higher-level meanings. Method In this paper, we propose the Recursive Convolutional Bayesian Model (RCBM) to address both of these fundamental questions. The key idea behind our approach consists of constructing a deep-learning framework using specialized convolution operators that are designed to exploit the inherent heterogeneity of social dynamics. RCBM’s runtime and convergence properties are guaranteed by formal analyses. Results Experimental results show that the proposed method outperforms the state-of-the-art approaches both in terms of solution quality and computational efficiency. Indeed, by applying the proposed method on two social network datasets, Twitter and Yelp, we are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. Finally, our analysis offers new insights on understanding and engineering social media dynamics, with direct applications to opinion spreading and online content promotion. PMID:25830775

Tinnitus-provoking salicylate treatment triggers social impairments in mice.

PubMed

Guitton, Matthieu J

2009-09-01

Tinnitus (perception of sound in silence) strongly affects the quality of life of sufferers. Tinnitus sufferers and their relatives frequently complain about major social impairments. However, it is not known whether this impairment directly results from the occurrence of tinnitus or is the indirect expression of a preexisting psychological vulnerability. Using the well-characterized animal model of salicylate-induced tinnitus, we investigate in mice whether the occurrence of tinnitus can trigger social impairments. Experiments were performed on 32 male Balb/C mice. Tinnitus was induced in mice using salicylate treatment. Social behavior was assessed in experimental and control animals using social interaction paradigm. Interaction time, number of social events, and number of nonsocial events were assessed in all animals. We demonstrate for the first time that treatment known to induce tinnitus triggers complex social impairments in mice. While salicylate-treated animals present a massive decrease in their overall social interactions compared to control untreated animals, they also display a paradoxal increase in the number of conspecific followings. Tinnitus can thus trigger a complex set of modifications of behavior, which will not only find their expression at the individual level, but also at the social level. Our results suggest that tinnitus can directly be a cause of psychosocial impairment in human and have strong implications for the clinical management of tinnitus sufferers.

Individual and Situational Factors Associated with Social Barriers for Persons with Mobility Impairment

ERIC Educational Resources Information Center

McCaughey, Tiffany

2009-01-01

Decades of research have examined factors involved in complex, and sometimes stressful, interpersonal interactions between individuals with and without disabilities. The present study applies structural equation modeling to test an integrative model of individual and situational factors affecting encounters between able-bodied college students and…

A New Funding Model for Extension

ERIC Educational Resources Information Center

Brown, Paul W.; Otto, Daniel M.; Ouart, Michael D.

2006-01-01

The traditional funding model of the Cooperative Extension System has been stretched to its limits by increasing demand for information and programs without concurrent increases in funding by the public sector. As the social, economic, and political environments have evolved and become more complex, extension is often asked to apply the expertise…

Socializing Giftedness: Toward an ACCEL-S Approach

ERIC Educational Resources Information Center

Glaveanu, Vlad P.; Kaufman, James C.

2017-01-01

In this response, we commend Sternberg's Active Concerned Citizenship and Ethical Leadership (ACCEL) model yet urge him to consider an ACCEL-S model that more fully incorporates society's integrative role in giftedness. ACCEL-S builds on the highly complex and contextual view of giftedness proposed by Sternberg and transforms it into a…

Guiding and Modelling Quality Improvement in Higher Education Institutions

ERIC Educational Resources Information Center

Little, Daniel

2015-01-01

The article considers the process of creating quality improvement in higher education institutions from the point of view of current organisational theory and social-science modelling techniques. The author considers the higher education institution as a functioning complex of rules, norms and other organisational features and reviews the social…

Youth Purpose through the Lens of the Theory of Organizing Models of Thinking

ERIC Educational Resources Information Center

Arantes, Valeria; Araujo, Ulisses; Pinheiro, Viviane; Moreno Marimon, Montserrat; Sastre, Genoveva

2017-01-01

Purpose represents a unique opportunity for identifying and analyzing the complexity of human reasoning, considering that its constitution brings together cognitive, affective and social elements. In this article, we use the Theory of Organizing Models of Thinking (OMT), an epistemological and methodological approach based on developmental…

Social relevance drives viewing behavior independent of low-level salience in rhesus macaques

PubMed Central

Solyst, James A.; Buffalo, Elizabeth A.

2014-01-01

Quantifying attention to social stimuli during the viewing of complex social scenes with eye tracking has proven to be a sensitive method in the diagnosis of autism spectrum disorders years before average clinical diagnosis. Rhesus macaques provide an ideal model for understanding the mechanisms underlying social viewing behavior, but to date no comparable behavioral task has been developed for use in monkeys. Using a novel scene-viewing task, we monitored the gaze of three rhesus macaques while they freely viewed well-controlled composed social scenes and analyzed the time spent viewing objects and monkeys. In each of six behavioral sessions, monkeys viewed a set of 90 images (540 unique scenes) with each image presented twice. In two-thirds of the repeated scenes, either a monkey or an object was replaced with a novel item (manipulated scenes). When viewing a repeated scene, monkeys made longer fixations and shorter saccades, shifting from a rapid orienting to global scene contents to a more local analysis of fewer items. In addition to this repetition effect, in manipulated scenes, monkeys demonstrated robust memory by spending more time viewing the replaced items. By analyzing attention to specific scene content, we found that monkeys strongly preferred to view conspecifics and that this was not related to their salience in terms of low-level image features. A model-free analysis of viewing statistics found that monkeys that were viewed earlier and longer had direct gaze and redder sex skin around their face and rump, two important visual social cues. These data provide a quantification of viewing strategy, memory and social preferences in rhesus macaques viewing complex social scenes, and they provide an important baseline with which to compare to the effects of therapeutics aimed at enhancing social cognition. PMID:25414633

Is the integration of nutritional care in the different assistance levels possible? The Catalan experience. Clinical perspective

PubMed

Burgos Peláez, Rosa; Joaquin Ortiz, Clara; Vaqué Crusellas, Cristina

2017-05-08

Disease-related malnutrition is highly prevalent in pathologies commonly integrating care complexity. Healthcare models for complexity must include malnutrition detection and approaches, since it is a key factor which has great impact on the patient’s evolution and the consumption of healthcare resources. Malnourished patients present higher hospitalization, complication and mortality rates, higher demand of post-discharge social resources and higher hospital readmission frequency. Detecting malnutrition is necessary to implement a nutritional care program which might be used in any assistance level. The integration of health and social care and the development of information tools which are shared by the different assistance agents has allowed the development of a program for the management of disease-related malnutrition in patients with clinical complexity in Catalonia.

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.

Creating an inclusive mall environment with the PRECEDE-PROCEED model: a living lab case study.

PubMed

Ahmed, Sara; Swaine, Bonnie; Milot, Marc; Gaudet, Caroline; Poldma, Tiiu; Bartlett, Gillian; Mazer, Barbara; Le Dorze, Guylaine; Barbic, Skye; Rodriguez, Ana Maria; Lefebvre, Hélène; Archambault, Philippe; Kairy, Dahlia; Fung, Joyce; Labbé, Delphine; Lamontagne, Anouk; Kehayia, Eva

2017-10-01

Although public environments provide opportunities for participation and social inclusion, they are not always inclusive spaces and may not accommodate the wide diversity of people. The Rehabilitation Living Lab in the Mall is a unique, interdisciplinary, and multi-sectoral research project with an aim to transform a shopping complex in Montreal, Canada, into an inclusive environment optimizing the participation and social inclusion of all people. The PRECEDE-PROCEDE Model (PPM), a community-oriented and participatory planning model, was applied as a framework. The PPM is comprised of nine steps divided between planning, implementation, and evaluation. The PPM is well suited as a framework for the development of an inclusive mall. Its ecological approach considers the environment, as well as the social and individual factors relating to mall users' needs and expectations. Transforming a mall to be more inclusive is a complex process involving many stakeholders. The PPM allows the synthesis of several sources of information, as well as the identification and prioritization of key issues to address. The PPM also helps to frame and drive the implementation and evaluate the components of the project. This knowledge can help others interested in using the PPM to create similar enabling and inclusive environments world-wide. Implication for rehabilitation While public environments provide opportunities for participation and social inclusion, they are not always inclusive spaces and may not accommodate the wide diversity of people. The PRECEDE PROCEDE Model (PPM) is well suited as a framework for the development, implementation, and evaluation of an inclusive mall. Environmental barriers can negatively impact the rehabilitation process by impeding the restoration and augmentation of function. Removing barriers to social participation and independent living by improving inclusivity in the mall and other environments positively impacts the lives of people with disabilities.

Functional Pathways of Social Support for Mental Health in Work and Family Domains Among Chinese Scientific and Technological Professionals.

PubMed

Gan, Yiqun; Gan, Tingting; Chen, Zhiyan; Miao, Miao; Zhang, Kan

2015-10-01

This study investigated the role of social support in the complex pattern of associations among stressors, work-family interferences and depression in the domains of work and family. A questionnaire was administered to a nationwide sample of 11,419 Chinese science and technology professionals. Several structural equation models were specified to determine whether social support functioned as a predictor or a mediator. Using Mplus 5.0, we compared the moderation model, the independence model, the antecedent model and the mediation model. The results revealed that the relationship between work-family interference and social support was domain specific. The independence model fit the data best in the work domain. Both the moderation model and the antecedent model fit the family domain data equally well. The current study was conducted to answer the need for comprehensive investigations of cultural uniqueness in the antecedents of work-family interference. The domain specificity, i.e. the multiple channels of the functions of support in the family domain and not in the work domain, ensures that this study is unique and culturally specific. Copyright © 2014 John Wiley & Sons, Ltd.

Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

PubMed

Frantz, Terrill L

2012-01-01

This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities. Copyright © 2012 S. Karger AG, Basel.

Measuring the Complexity of Teachers' Enactment of Practice for Equity: A Rasch Model and Facet Theory-Based Approach

ERIC Educational Resources Information Center

Chang, Wen-Chia Claire

2017-01-01

Preparing and supporting teachers to enact teaching practice that responds to diversity, challenges educational inequities, and promotes social justice is a pressing yet daunting and complex task. More research is needed to understand how and to what extent teacher education programs prepare and support teacher candidates to enhance the…

Progress in wilderness fire science: Embracing complexity

Treesearch

Carol Miller; Gregory H. Aplet

2016-01-01

Wilderness has played an invaluable role in the development of wildland fire science. Since Agee’s review of the subject 15 years ago, tremendous progress has been made in the development of models and data, in understanding the complexity of wildland fire as a landscape process, and in appreciating the social factors that influence the use of wilderness fire....

Neurobehavioral assessment of maternal odor in developing rat pups: implications for social buffering.

PubMed

Al Aïn, Syrina; Perry, Rosemarie E; Nuñez, Bestina; Kayser, Kassandra; Hochman, Chase; Brehman, Elizabeth; LaComb, Miranda; Wilson, Donald A; Sullivan, Regina M

2017-02-01

Social support can attenuate the behavioral and stress hormone response to threat, a phenomenon called social buffering. The mother's social buffering of the infant is one of the more robust examples; yet we understand little about the neurobiology. Using a rodent model, we explore the neurobiology of social buffering by assessing neural processing of the maternal odor, a major cue controlling social buffering in rat pups. We used pups before (postnatal day (PN) 7) and after (PN14, PN23) the functional emergence of social buffering. Pups were injected with 14 C 2-deoxyglucose (2-DG) and presented with the maternal odor, a control preferred odor incapable of social buffering (acetophenone), or no odor. Brains were removed, processed for autoradiography and brain areas identified as important in adult social buffering were assessed, including the amygdala basolateral complex (Basolateral Amygdala [BLA]), medial prefrontal cortex (mPFC), and anterior cingulate cortex (ACC). Results suggest dramatic changes in the processing of maternal odor. PN7 pups show mPFC and ACC activation, although PN14 pups showed no activation of the mPFC, ACC, or BLA. All brain areas assessed were recruited by PN23. Additional analysis suggests substantial changes in functional connectivity across development. Together, these results imply complex nonlinear transitions in the neurobiology of social buffering in early life that may provide insight into the changing role of the mother in supporting social buffering.

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

Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques

PubMed Central

Madlon-Kay, Seth; Brent, Lauren J. N.; Heller, Katherine A.; Platt, Michael L.

2017-01-01

Investigating the biological bases of social phenotypes is challenging because social behavior is both high-dimensional and richly structured, and biological factors are more likely to influence complex patterns of behavior rather than any single behavior in isolation. The space of all possible patterns of interactions among behaviors is too large to investigate using conventional statistical methods. In order to quantitatively define social phenotypes from natural behavior, we developed a machine learning model to identify and measure patterns of behavior in naturalistic observational data, as well as their relationships to biological, environmental, and demographic sources of variation. We applied this model to extensive observations of natural behavior in free-ranging rhesus macaques, and identified behavioral states that appeared to capture periods of social isolation, competition over food, conflicts among groups, and affiliative coexistence. Phenotypes, represented as the rate of being in each state for a particular animal, were strongly and broadly influenced by dominance rank, sex, and social group membership. We also identified two states for which variation in rates had a substantial genetic component. We discuss how this model can be extended to identify the contributions to social phenotypes of particular genetic pathways. PMID:28754001

Relations among Teachers’ Emotion Socialization Beliefs and Practices, and Preschoolers’ Emotional Competence

PubMed Central

Morris, Carol A.S.; Denham, Susanne A.; Bassett, Hideko H.; Curby, Timothy W.

2013-01-01

Research Findings Utilizing a three-part model of emotion socialization that includes Modeling, Contingent Responding, and Teaching, this study examined the associations between 44 teachers’ self-reported and observed emotion socialization practices and 326 preschoolers’ emotion knowledge and observed emotional behavior. Multi-level analyses revealed that the majority of the variance in the children’s emotion knowledge scores and observed emotional behavior was predicted by factors within, rather than between, classrooms. Teachers’ use of all three emotion socialization techniques did contribute to the prediction of the children’s scores; however, the nature of these associations differed by children’s age and gender. Practice or Policy The development of children’s emotional competence is a complex, multi-faceted process in which many interaction partners play a role; early childhood teachers act as emotion socialization agents for the children in their care by modeling emotions, responding either supportively or punitively to children’s expressions of emotions, and engaging in direct instruction regarding emotional experience. This research may provide a basis for potential future interventions designed to assist teachers in developing their own emotion socialization skills so that they can be more effective emotion socialization agents for the children in their care. PMID:24159256

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.

An Ontology of Power: Perception and Reality in Conflict

DTIC Science & Technology

2016-12-01

synthetic model was developed as the constant comparative analysis was resumed through the application of selected theory toward the original source...The synthetic model represents a series of maxims for the analysis of a complex social system, developed through a study of contemporary national...and categories. A model of strategic agency is proposed as an alternative framework for developing security strategy. The strategic agency model draws

Secondary students' use of social and natural world information in a land use decision context

NASA Astrophysics Data System (ADS)

Kumler, Laura M.

Many societal problems, including land use issues, are complex integrated human-ecological challenges that require an understanding of social and natural world connections. This dissertation investigates how secondary students perceive the social and natural world dimensions of land use, how they might act to support sustainable land use, and how Kaplan and Kaplan's (2008) Reasonable Person Model can inform teaching approaches to prepare students for such complex decisions and action-taking. The dissertation argues that subject compartmentalization in high schools adversely impacts students' abilities to use and to integrate information from various subjects to make a land use decision. Nine secondary science and social studies teachers and their students (n=500) participated in a quasi-experiment using pre- and posttests with treatment and comparison groups to gauge students' requests for social versus natural world information to make land use decisions. Students' self-reported actions and knowledge of actions to support sustainable land use were also measured. Additional data included classroom observations, teacher logs and interviews, and 52 student interviews. Results indicated that students requested social world over natural world information and preferred to consult with social scientists and stakeholders over natural scientists. Results also suggested that experiencing an integrated curriculum increased students' requests for natural world information relevant to the land use decision. Interestingly, this effect occurred even among social studies students whose teachers reported putting scant emphasis on the natural world curriculum content. Moreover, the type of course in which students experienced the curriculum predicted student information use. Finally, students were found to have a limited repertoire of land use actions and knowledge of actions and generally reported undertaking and thinking of individual actions such as recycling or trash pick-up rather than collective actions or political, consumer, or information-sharing actions. The curriculum had only a limited impact on students' actions and knowledge of actions, possibly because teachers did not engage students in actions. The concluding chapter discusses these results in the context of the Reasonable Person Model. The model suggests that cognitive needs, including mental model building, exploration, and meaningful participation, are mutually reinforcing and when provided for can enhance student learning outcomes.

Social Identity Complexity, Cross-ethnic Friendships, and Intergroup Attitudes in Urban Middle Schools

PubMed Central

Knifsend, Casey A.; Juvonen, Jaana

2013-01-01

The current study investigated contextual antecedents (i.e., cross-ethnic peers and friends) and correlates (i.e., intergroup attitudes) of social identity complexity in seventh grade. Social identity complexity refers to the perceived overlap among social groups with which youth identify. Identifying mostly with out-of-school sports, religious affiliations, and peer crowds, the ethnically diverse sample (N = 622; Mage in seventh grade = 12.56) showed moderately high complexity. Social identity complexity mediated the link between cross-ethnic friendships and ethnic intergroup attitudes, but only when adolescents had a high proportion of cross-ethnic peers at school. Results are discussed in terms of how school diversity can promote complex social identities and positive intergroup attitudes. PMID:24032401

Fuzzy cognitive mapping in support of integrated ecosystem assessments: Developing a shared conceptual model among stakeholders.

PubMed

Vasslides, James M; Jensen, Olaf P

2016-01-15

Ecosystem-based approaches, including integrated ecosystem assessments, are a popular methodology being used to holistically address management issues in social-ecological systems worldwide. In this study we utilized fuzzy logic cognitive mapping to develop conceptual models of a complex estuarine system among four stakeholder groups. The average number of categories in an individual map was not significantly different among groups, and there were no significant differences between the groups in the average complexity or density indices of the individual maps. When ordered by their complexity scores, eight categories contributed to the top four rankings of the stakeholder groups, with six of the categories shared by at least half of the groups. While non-metric multidimensional scaling (nMDS) analysis displayed a high degree of overlap between the individual models across groups, there was also diversity within each stakeholder group. These findings suggest that while all of the stakeholders interviewed perceive the subject ecosystem as a complex series of social and ecological interconnections, there are a core set of components that are present in most of the groups' models that are crucial in managing the system towards some desired outcome. However, the variability in the connections between these core components and the rest of the categories influences the exact nature of these outcomes. Understanding the reasons behind these differences will be critical to developing a shared conceptual model that will be acceptable to all stakeholder groups and can serve as the basis for an integrated ecosystem assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.

"Speaking the dialect": understanding public discourse in the aftermath of an HIV vaccine trial shutdown.

PubMed

Newman, Peter A; Logie, Carmen; James, Llana; Charles, Tamicka; Maxwell, John; Salam, Khaled; Woodford, Michael

2011-09-01

We investigated how persons from key populations at higher risk of HIV exposure interpreted the process and outcomes of the Step Study HIV-1 vaccine trial, which was terminated early, and implications for willingness to participate in and community support for HIV vaccine research. We used qualitative methods and a community-based approach in 9 focus groups (n = 72) among ethnically and sexually diverse populations and 6 semistructured key informant interviews in Ontario, Canada, in 2007 to 2008. Participants construed social meaning from complex clinical and biomedical phenomena. Social representations and mental models emerged in fears of vaccine-induced infection, conceptualizations of unfair recruitment practices and increased risk behaviors among trial participants, and questioning of informed consent. Narratives of altruism and the common good demonstrated support for future trials. Public discourse on HIV vaccine trials is a productive means of interpreting complex clinical trial processes and outcomes in the context of existing beliefs and experiences regarding HIV vaccines, medical research, and historical disenfranchisement. Strategic engagement with social representations and mental models may promote meaningful community involvement in biomedical HIV prevention research.

Model of community emergence in weighted social networks

NASA Astrophysics Data System (ADS)

Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

2009-04-01

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

Contagion on complex networks with persuasion

NASA Astrophysics Data System (ADS)

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-03-01

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

Contagion on complex networks with persuasion

PubMed Central

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-01-01

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense. PMID:27029498

Contagion on complex networks with persuasion.

PubMed

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-03-31

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

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.

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.

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

Hospital graduate social work field work programs: a study in New York City.

PubMed

Showers, N

1990-02-01

Twenty-seven hospital field work programs in New York City were studied. Questionnaires were administered to program coordinators and 238 graduate social work students participating in study programs. High degrees of program structural complexity and variation were found, indicating a state of art well beyond that described in the general field work literature. High rates of student satisfaction with learning, field instructors, programs, and the overall field work experience found suggest that the complexity of study programs may be more effective than traditional field work models. Statistically nonsignificant study findings indicate areas in which hospital social work departments may develop field work programs consistent with shifting organizational needs, without undue risk to educational effectiveness. Statistically significant findings suggest areas in which inflexibility in program design may be more beneficial in the diagnostic related groups era.

Building out a Measurement Model to Incorporate Complexities of Testing in the Language Domain

ERIC Educational Resources Information Center

Wilson, Mark; Moore, Stephen

2011-01-01

This paper provides a summary of a novel and integrated way to think about the item response models (most often used in measurement applications in social science areas such as psychology, education, and especially testing of various kinds) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. In addition,…

Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

PubMed

Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

2017-02-07

Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimizing the health impacts of civil legal aid interventions: the public health framework of medical-legal partnerships.

PubMed

Lawton, Ellen; Tyler, Elizabeth Tobin

2013-07-01

Research documents the significance of the social determinants of health - the social and environmental conditions in which people live, work and play. A critical foundation of these social and environmental conditions are laws and regulations, which construct the environments in which individuals and populations live, influencing how and when people face disease. Increasingly, healthcare providers, public health professionals and lawyers concerned with social determinants are joining forces to form Medical-Legal Partnerships (MLPs) which offer a preventive approach to address the complex social, legal and systemic problems that affect the health of vulnerable populations. Now in more than 500 health and legal institutions across the country, including Rhode Island, MLP is a healthcare delivery model that integrates legal assistance as a vital component of healthcare. This article explores the many benefits of the MLP model for improving patient health, transforming medical and legal practice and institutions and generating policy changes that specifically address health disparities and social determinants.

Oxytocin and social cognition in rhesus macaques: Implications for understanding and treating human psychopathology

PubMed Central

Chang, Steve W. C.; Platt, Michael L.

2013-01-01

Converging evidence from humans and non-human animals indicates that the neurohypophysial hormone oxytocin (OT) evolved to serve a specialized function in social behavior in mammals. Although OT-based therapies are currently being evaluated as remedies for social deficits in neuropsychiatric disorders, precisely how OT regulates complex social processes remains largely unknown. Here we describe how a non-human primate model can be used to understand the mechanisms by which OT regulates social cognition and thereby inform its clinical application in humans. We focus primarily on recent advances in our understanding of OT-mediated social cognition in rhesus macaques (Macaca mulatta), supplemented by discussion of recent work in humans, other primates, and rodents. Together, these studies endorse the hypothesis that OT promotes social exploration both by amplifying social motivation and by attenuating social vigilance. PMID:24231551

An overview of structurally complex network-based modeling of public opinion in the “We the Media” era

NASA Astrophysics Data System (ADS)

Wang, Guanghui; Wang, Yufei; Liu, Yijun; Chi, Yuxue

2018-05-01

As the transmission of public opinion on the Internet in the “We the Media” era tends to be supraterritorial, concealed and complex, the traditional “point-to-surface” transmission of information has been transformed into “point-to-point” reciprocal transmission. A foundation for studies of the evolution of public opinion and its transmission on the Internet in the “We the Media” era can be laid by converting the massive amounts of fragmented information on public opinion that exists on “We the Media” platforms into structurally complex networks of information. This paper describes studies of structurally complex network-based modeling of public opinion on the Internet in the “We the Media” era from the perspective of the development and evolution of complex networks. The progress that has been made in research projects relevant to the structural modeling of public opinion on the Internet is comprehensively summarized. The review considers aspects such as regular grid-based modeling of the rules that describe the propagation of public opinion on the Internet in the “We the Media” era, social network modeling, dynamic network modeling, and supernetwork modeling. Moreover, an outlook for future studies that address complex network-based modeling of public opinion on the Internet is put forward as a summary from the perspective of modeling conducted using the techniques mentioned above.

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.

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

Enterprise Systems Analysis

DTIC Science & Technology

2016-03-14

flows , or continuous state changes, with feedback loops and lags modeled in the flow system. Agent based simulations operate using a discrete event...DeLand, S. M., Rutherford, B . M., Diegert, K. V., & Alvin, K. F. (2002). Error and uncertainty in modeling and simulation . Reliability Engineering...intrinsic complexity of the underlying social systems fundamentally limits the ability to make

Integrated Services for Frail Elders (SIPA): A Trial of a Model for Canada

ERIC Educational Resources Information Center

Beland, Francois; Bergman, Howard; Lebel, Paule; Dallaire, Luc; Fletcher, John; Contandriopoulos, Andre-Pierre; Solidage, Tousignant Pierre

2006-01-01

The complex formed by chronic illness, episodes of acute illness, physiological disabilities, functional limitations, and cognitive problems is prevalent among frail elderly persons. These individuals rely on assistance from social and health care programs, which in Canada are still fragmented. SIPA is an integrated service model based on…

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…

A Socioecological Model of Rape Survivors' Decisions to Aid in Case Prosecution

ERIC Educational Resources Information Center

Anders, Mary C.; Christopher, F. Scott

2011-01-01

The purpose of our study was to identify factors underlying rape survivors' post-assault prosecution decisions by testing a decision model that included the complex relations between the multiple social ecological systems within which rape survivors are embedded. We coded 440 police rape cases for characteristics of the assault and characteristics…

Open-Ended Learning Environments: A Theoretical Framework and Model for Design.

ERIC Educational Resources Information Center

Hill, Janette R.; Land, Susan M.

This paper presents a framework and model for design of open-ended learning environments (OELEs). First, an overview is presented that addresses key characteristics of OELEs, including: use of meaningful, complex contexts; provision of tools and resources; learner reflection and self-monitoring; and social, material, or technological scaffolding.…

A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

PubMed

Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

2017-06-16

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

Neuroanatomical Substrates of Rodent Social Behavior: The Medial Prefrontal Cortex and Its Projection Patterns.

PubMed

Ko, Jaewon

2017-01-01

Social behavior encompasses a number of distinctive and complex constructs that form the core elements of human imitative culture, mainly represented as either affiliative or antagonistic interactions with conspecifics. Traditionally considered in the realm of psychology, social behavior research has benefited from recent advancements in neuroscience that have accelerated identification of the neural systems, circuits, causative genes and molecular mechanisms that underlie distinct social cognitive traits. In this review article, I summarize recent findings regarding the neuroanatomical substrates of key social behaviors, focusing on results from experiments conducted in rodent models. In particular, I will review the role of the medial prefrontal cortex (mPFC) and downstream subcortical structures in controlling social behavior, and discuss pertinent future research perspectives.

Neuroanatomical Substrates of Rodent Social Behavior: The Medial Prefrontal Cortex and Its Projection Patterns

PubMed Central

Ko, Jaewon

2017-01-01

Social behavior encompasses a number of distinctive and complex constructs that form the core elements of human imitative culture, mainly represented as either affiliative or antagonistic interactions with conspecifics. Traditionally considered in the realm of psychology, social behavior research has benefited from recent advancements in neuroscience that have accelerated identification of the neural systems, circuits, causative genes and molecular mechanisms that underlie distinct social cognitive traits. In this review article, I summarize recent findings regarding the neuroanatomical substrates of key social behaviors, focusing on results from experiments conducted in rodent models. In particular, I will review the role of the medial prefrontal cortex (mPFC) and downstream subcortical structures in controlling social behavior, and discuss pertinent future research perspectives. PMID:28659766

Addressing the determinants of child mental health: intersectionality as a guide to primary health care renewal.

PubMed

McPherson, Charmaine M; McGibbon, Elizabeth A

2010-09-01

Primary health care (PHC) renewal was designed explicitly to attend to the multidimensional factors impacting on health, including the social determinants of health. These determinants are central considerations in the development of integrated, cross-sectoral, and multi-jurisdictional policies such as those that inform models of shared mental health care for children. However, there are complex theoretical challenges in translating these multidimensional issues into policy. One of these is the rarely discussed interrelationships among the social determinants of health and identities such as race, gender, age, sexuality, and social class within the added confluence of geographic contexts. An intersectionality lens is used to examine the complex interrelationships among the factors affecting child mental health and the associated policy challenges surrounding PHC renewal. The authors argue that an understanding of the intersections of social determinants of health, identity, and geography is pivotal in guiding policy-makers as they address child mental health inequities using a PHC renewal agenda.

Organized All the Way Down

NASA Astrophysics Data System (ADS)

Sylvan, David

At least since Adam Smith's The Wealth of Nations, it has been understood that social systems can be considered as having emergent properties not reducible to the actions of individuals. The appeal of this idea is obvious, no different now than in Smith's time: that aggregates of persons can be ordered without such order being intended or enforced by any particular person or persons. A search for such an "invisible hand" is what brings many of us to the study of complexity and the construction of various types of computational models aimed at capturing it. However, in proceeding along these lines, we have tended to focus on particular types of social systems — what I will in this paper call "thin" systems, such as markets and populations — and ignored other types, such as groups, whose base interactions are "thick," i.e., constructed as one of many possibilities, by the participants, at the moment in which they take place. These latter systems are not only ubiquitous but pose particular modeling problems for students of complexity: the local interactions are themselves complex and the systems display no strongly emergent features.

Structural Preferential Attachment: Network Organization beyond the Link

NASA Astrophysics Data System (ADS)

Hébert-Dufresne, Laurent; Allard, Antoine; Marceau, Vincent; Noël, Pierre-André; Dubé, Louis J.

2011-10-01

We introduce a mechanism which models the emergence of the universal properties of complex networks, such as scale independence, modularity and self-similarity, and unifies them under a scale-free organization beyond the link. This brings a new perspective on network organization where communities, instead of links, are the fundamental building blocks of complex systems. We show how our simple model can reproduce social and information networks by predicting their community structure and more importantly, how their nodes or communities are interconnected, often in a self-similar manner.

Implementation of a Transdisciplinary Team for the Transition Support of Medically and Socially Complex Youth.

PubMed

Ciccarelli, Mary R; Gladstone, Erin B; Armstrong Richardson, Eprise A J

2015-01-01

This article reports the ongoing work of a statewide transition support program which serves youth ages 11 to 22 with medically complex conditions and socially complex lives. Seven years of transition support services have led to program evolution demonstrated via a descriptive summary of the patients along with both families' and primary care providers' responses to satisfaction surveys. An illustrative case is used to highlight the types of expertise needed in specialized transition service delivery for patients with significant complexity. The team's analysis of their transdisciplinary work processes further explains the work. Nearly three hundred youth with complex needs are served yearly. Families and primary care providers express high satisfaction with the support of the services. The case example shows the broad array of transition-specific services engaged beyond the usual skill set of pediatric or adult care coordination teams. Transdisciplinary team uses skills in collaboration, support, learning, and compromise within a trusting and respectful environment. They describe the shared responsibility and continuous learning of the whole team. Youth with complex medical conditions and complex social situations are at higher risk for problems during transition. Serving this population with a transdisciplinary model is time consuming and requires advanced expertise but, with those investments, we can meet the expectations of the youth, their families and primary care providers. Successful transdisciplinary teamwork requires sustained and focused investment. Further work is needed to describe the complexity of this service delivery along with distinct transition outcomes and costs comparisons. Copyright © 2015 Elsevier Inc. All rights reserved.

Wolves, dogs, rearing and reinforcement: complex interactions underlying species differences in training and problem-solving performance.

PubMed

Frank, Harry

2011-11-01

Frank and Frank et al. (1982-1987) administered a series of age-graded training and problem-solving tasks to samples of Eastern timber wolf (C. lupus lycaon) and Alaskan Malamute (C. familiaris) pups to test Frank's (Zeitschrift für Tierpsychologie 53:389-399, 1980) model of the evolution of information processing under conditions of natural and artificial selection. Results confirmed the model's prediction that wolves should perform better than dogs on problem-solving tasks and that dogs should perform better than wolves on training tasks. Further data collected at the University of Connecticut in 1983 revealed a more complex and refined picture, indicating that species differences can be mediated by a number of factors influencing wolf performance, including socialization regimen (hand-rearing vs. mother-rearing), interactive effects of socialization on the efficacy of both rewards and punishments, and the flexibility to select learning strategies that experimenters might not anticipate.

Evolutionary transitions towards eusociality in snapping shrimps.

PubMed

Chak, Solomon Tin Chi; Duffy, J Emmett; Hultgren, Kristin M; Rubenstein, Dustin R

2017-03-20

Animal social organization varies from complex societies where reproduction is dominated by a single individual (eusociality) to those where reproduction is more evenly distributed among group members (communal breeding). Yet, how simple groups transition evolutionarily to more complex societies remains unclear. Competing hypotheses suggest that eusociality and communal breeding are alternative evolutionary endpoints, or that communal breeding is an intermediate stage in the transition towards eusociality. We tested these alternative hypotheses in sponge-dwelling shrimps, Synalpheus spp. Although species varied continuously in reproductive skew, they clustered into pair-forming, communal and eusocial categories based on several demographic traits. Evolutionary transition models suggested that eusocial and communal species are discrete evolutionary endpoints that evolved independently from pair-forming ancestors along alternative paths. This 'family-centred' origin of eusociality parallels observations in insects and vertebrates, reinforcing the role of kin selection in the evolution of eusociality and suggesting a general model of animal social evolution.

Energy Landscape of Social Balance

NASA Astrophysics Data System (ADS)

Marvel, Seth A.; Strogatz, Steven H.; Kleinberg, Jon M.

2009-11-01

We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social “balance” allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.

Energy landscape of social balance.

PubMed

Marvel, Seth A; Strogatz, Steven H; Kleinberg, Jon M

2009-11-06

We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social "balance" allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.

Friendship quality, social preference, proximity prestige, and self-perceived social competence: interactive influences on children's loneliness.

PubMed

Zhang, Fengjuan; You, Zhiqi; Fan, Cuiying; Gao, Chuang; Cohen, Robert; Hsueh, Yeh; Zhou, Zongkui

2014-10-01

The purpose of this study was to test an integrative model in which peer relations at different levels of social complexity (friendship quality, social preference, and proximity prestige) are associated with children's loneliness, with children's self-perceived social competence acting as a mediator of these associations. A middle childhood sample of 509 Chinese children (233 girls and 276 boys; 3rd to 6th grade) completed a battery of sociometric and self-report questionnaires. Bootstrap analysis showed that self-perceived social competence mediated the relations between each peer variable and loneliness. In the integrative model tested with SEM, the mediating effect of self-perceived social competence in the relation between friendship quality and loneliness and between social preference and loneliness remained significant. However, self-perceived social competence no longer mediated the association between proximity prestige and loneliness, when considering the simultaneous influences of the three peer variables (friendship quality, social preference, and proximity prestige). The whole model accounted for 56% of the variance in loneliness. These findings suggest that self-perceived social competence played an important role in children's loneliness, that the quality and the quantity of direct peer relations (friendship quality, social preference, and part of proximity prestige) were associated with loneliness, and that indirect friends had a relatively lower but significant influence on children's loneliness. The results are discussed in terms of their implications for preventing children's loneliness. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

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.

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.

Ethanol-Induced Effects on Sting Extension Response and Punishment Learning in the Western Honey Bee (Apis mellifera)

PubMed Central

Giannoni-Guzmán, Manuel A.; Giray, Tugrul; Agosto-Rivera, Jose Luis; Stevison, Blake K.; Freeman, Brett; Ricci, Paige; Brown, Erika A.; Abramson, Charles I.

2014-01-01

Acute ethanol administration is associated with sedation and analgesia as well as behavioral disinhibition and memory loss but the mechanisms underlying these effects remain to be elucidated. During the past decade, insects have emerged as important model systems to understand the neural and genetic bases of alcohol effects. However, novel assays to assess ethanol's effects on complex behaviors in social or isolated contexts are necessary. Here we used the honey bee as an especially relevant model system since bees are typically exposed to ethanol in nature when collecting standing nectar crop of flowers, and there is recent evidence for independent biological significance of this exposure for social behavior. Bee's inhibitory control of the sting extension response (SER) and a conditioned-place aversion assay were used to study ethanol effects on analgesia, behavioral disinhibition, and associative learning. Our findings indicate that although ethanol, in a dose-dependent manner, increases SER thresholds (analgesic effects), it disrupts the ability of honey bees to inhibit SER and to associate aversive stimuli with their environment. These results suggest that ethanol's effects on analgesia, behavioral disinhibition and associative learning are common across vertebrates and invertebrates. These results add to the use of honey bees as an ethanol model to understand ethanol's effects on complex, socially relevant behaviors. PMID:24988309

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

Coarse cluster enhancing collaborative recommendation for social network systems

NASA Astrophysics Data System (ADS)

Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

2017-10-01

Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

Factors Associated With Having a Physician, Nurse Practitioner, or Physician Assistant as Primary Care Provider for Veterans With Diabetes Mellitus

PubMed Central

Morgan, Perri; Everett, Christine M.; Smith, Valerie A.; Woolson, Sandra; Edelman, David; Hendrix, Cristina C.; Berkowitz, Theodore S. Z.; White, Brandolyn; Jackson, George L.

2017-01-01

Expanded use of nurse practitioners (NPs) and physician assistants (PAs) is a potential solution to workforce issues, but little is known about how NPs and PAs can best be used. Our study examines whether medical and social complexity of patients is associated with whether their primary care provider (PCP) type is a physician, NP, or PA. In this national retrospective cohort study, we use 2012-2013 national Veterans Administration (VA) electronic health record data from 374 223 veterans to examine whether PCP type is associated with patient, clinic, and state-level factors representing medical and social complexity, adjusting for all variables simultaneously using a generalized logit model. Results indicate that patients with physician PCPs are modestly more medically complex than those with NP or PA PCPs. For the group having a Diagnostic Cost Group (DCG) score >2.0 compared with the group having DCG <0.5, odds of having an NP or a PA were lower than for having a physician PCP (NP odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.79-0.88; PA OR = 0.85, CI: 0.80-0.89). Social complexity is not consistently associated with PCP type. Overall, we found minor differences in provider type assignment. This study improves on previous work by using a large national dataset that accurately ascribes the work of NPs and PAs, analyzing at the patient level, analyzing NPs and PAs separately, and addressing social as well as medical complexity. This is a requisite step toward studies that compare patient outcomes by provider type. PMID:28617196

Factors Associated With Having a Physician, Nurse Practitioner, or Physician Assistant as Primary Care Provider for Veterans With Diabetes Mellitus.

PubMed

Morgan, Perri; Everett, Christine M; Smith, Valerie A; Woolson, Sandra; Edelman, David; Hendrix, Cristina C; Berkowitz, Theodore S Z; White, Brandolyn; Jackson, George L

2017-01-01

Expanded use of nurse practitioners (NPs) and physician assistants (PAs) is a potential solution to workforce issues, but little is known about how NPs and PAs can best be used. Our study examines whether medical and social complexity of patients is associated with whether their primary care provider (PCP) type is a physician, NP, or PA. In this national retrospective cohort study, we use 2012-2013 national Veterans Administration (VA) electronic health record data from 374 223 veterans to examine whether PCP type is associated with patient, clinic, and state-level factors representing medical and social complexity, adjusting for all variables simultaneously using a generalized logit model. Results indicate that patients with physician PCPs are modestly more medically complex than those with NP or PA PCPs. For the group having a Diagnostic Cost Group (DCG) score >2.0 compared with the group having DCG <0.5, odds of having an NP or a PA were lower than for having a physician PCP (NP odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.79-0.88; PA OR = 0.85, CI: 0.80-0.89). Social complexity is not consistently associated with PCP type. Overall, we found minor differences in provider type assignment. This study improves on previous work by using a large national dataset that accurately ascribes the work of NPs and PAs, analyzing at the patient level, analyzing NPs and PAs separately, and addressing social as well as medical complexity. This is a requisite step toward studies that compare patient outcomes by provider type.

Statistical methods applied to the study of opinion formation models: a brief overview and results of a numerical study of a model based on the social impact theory

NASA Astrophysics Data System (ADS)

Bordogna, Clelia María; Albano, Ezequiel V.

2007-02-01

The aim of this paper is twofold. On the one hand we present a brief overview on the application of statistical physics methods to the modelling of social phenomena focusing our attention on models for opinion formation. On the other hand, we discuss and present original results of a model for opinion formation based on the social impact theory developed by Latané. The presented model accounts for the interaction among the members of a social group under the competitive influence of a strong leader and the mass media, both supporting two different states of opinion. Extensive simulations of the model are presented, showing that they led to the observation of a rich scenery of complex behaviour including, among others, critical behaviour and phase transitions between a state of opinion dominated by the leader and another dominated by the mass media. The occurrence of interesting finite-size effects reveals that, in small communities, the opinion of the leader may prevail over that of the mass media. This observation is relevant for the understanding of social phenomena involving a finite number of individuals, in contrast to actual physical phase transitions that take place in the thermodynamic limit. Finally, we give a brief outlook of open questions and lines for future work.

Oxytocin and vasopressin: linking pituitary neuropeptides and their receptors to social neurocircuits

PubMed Central

Baribeau, Danielle A.; Anagnostou, Evdokia

2015-01-01

Oxytocin and vasopressin are pituitary neuropeptides that have been shown to affect social processes in mammals. There is growing interest in these molecules and their receptors as potential precipitants of, and/or treatments for, social deficits in neurodevelopmental disorders, including autism spectrum disorder. Numerous behavioral-genetic studies suggest that there is an association between these peptides and individual social abilities; however, an explanatory model that links hormonal activity at the receptor level to complex human behavior remains elusive. The following review summarizes the known associations between the oxytocin and vasopressin neuropeptide systems and social neurocircuits in the brain. Following a micro- to macro- level trajectory, current literature on the synthesis and secretion of these peptides, and the structure, function and distribution of their respective receptors is first surveyed. Next, current models regarding the mechanism of action of these peptides on microcircuitry and other neurotransmitter systems are discussed. Functional neuroimaging evidence on the acute effects of exogenous administration of these peptides on brain activity is then reviewed. Overall, a model in which the local neuromodulatory effects of pituitary neuropeptides on brainstem and basal forebrain regions strengthen signaling within social neurocircuits proves appealing. However, these findings are derived from animal models; more research is needed to clarify the relevance of these mechanisms to human behavior and treatment of social deficits in neuropsychiatric disorders. PMID:26441508

Oxytocin and vasopressin: linking pituitary neuropeptides and their receptors to social neurocircuits.

PubMed

Baribeau, Danielle A; Anagnostou, Evdokia

2015-01-01

Oxytocin and vasopressin are pituitary neuropeptides that have been shown to affect social processes in mammals. There is growing interest in these molecules and their receptors as potential precipitants of, and/or treatments for, social deficits in neurodevelopmental disorders, including autism spectrum disorder. Numerous behavioral-genetic studies suggest that there is an association between these peptides and individual social abilities; however, an explanatory model that links hormonal activity at the receptor level to complex human behavior remains elusive. The following review summarizes the known associations between the oxytocin and vasopressin neuropeptide systems and social neurocircuits in the brain. Following a micro- to macro- level trajectory, current literature on the synthesis and secretion of these peptides, and the structure, function and distribution of their respective receptors is first surveyed. Next, current models regarding the mechanism of action of these peptides on microcircuitry and other neurotransmitter systems are discussed. Functional neuroimaging evidence on the acute effects of exogenous administration of these peptides on brain activity is then reviewed. Overall, a model in which the local neuromodulatory effects of pituitary neuropeptides on brainstem and basal forebrain regions strengthen signaling within social neurocircuits proves appealing. However, these findings are derived from animal models; more research is needed to clarify the relevance of these mechanisms to human behavior and treatment of social deficits in neuropsychiatric disorders.

Virtual social interactions in social anxiety--the impact of sex, gaze, and interpersonal distance.

PubMed

Wieser, Matthias J; Pauli, Paul; Grosseibl, Miriam; Molzow, Ina; Mühlberger, Andreas

2010-10-01

In social interactions, interpersonal distance between interaction partners plays an important role in determining the status of the relationship. Interpersonal distance is an important nonverbal behavior, and is used to regulate personal space in a complex interplay with other nonverbal behaviors such as eye gaze. In social anxiety, studies regarding the impact of interpersonal distance on within-situation avoidance behavior are so far rare. Thus the present study aimed to scrutinize the relationship between gaze direction, sex, interpersonal distance, and social anxiety in social interactions. Social interactions were modeled in a virtual-reality (VR) environment, where 20 low and 19 high socially anxious women were confronted with approaching male and female characters, who stopped in front of the participant, either some distance away or close to them, and displayed either a direct or an averted gaze. Gaze and head movements, as well as heart rate, were measured as indices of avoidance behavior and fear reactions. High socially anxious participants showed a complex pattern of avoidance behavior: when the avatar was standing farther away, high socially anxious women avoided gaze contact with male avatars showing a direct gaze. Furthermore, they showed avoidance behavior (backward head movements) in response to male avatars showing a direct gaze, regardless of the interpersonal distance. Overall, the current study proved that VR social interactions might be a very useful tool for investigating avoidance behavior of socially anxious individuals in highly controlled situations. This might also be the first step in using VR social interactions in clinical protocols for the therapy of social anxiety disorder.

Empirical Models of Social Learning in a Large, Evolving Network.

PubMed

Bener, Ayşe Başar; Çağlayan, Bora; Henry, Adam Douglas; Prałat, Paweł

2016-01-01

This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

Social interaction shapes babbling: Testing parallels between birdsong and speech

NASA Astrophysics Data System (ADS)

Goldstein, Michael H.; King, Andrew P.; West, Meredith J.

2003-06-01

Birdsong is considered a model of human speech development at behavioral and neural levels. Few direct tests of the proposed analogs exist, however. Here we test a mechanism of phonological development in human infants that is based on social shaping, a selective learning process first documented in songbirds. By manipulating mothers' reactions to their 8-month-old infants' vocalizations, we demonstrate that phonological features of babbling are sensitive to nonimitative social stimulation. Contingent, but not noncontingent, maternal behavior facilitates more complex and mature vocal behavior. Changes in vocalizations persist after the manipulation. The data show that human infants use social feedback, facilitating immediate transitions in vocal behavior. Social interaction creates rapid shifts to developmentally more advanced sounds. These transitions mirror the normal development of speech, supporting the predictions of the avian social shaping model. These data provide strong support for a parallel in function between vocal precursors of songbirds and infants. Because imitation is usually considered the mechanism for vocal learning in both taxa, the findings introduce social shaping as a general process underlying the development of speech and song.

Empirical Models of Social Learning in a Large, Evolving Network

PubMed Central

Bener, Ayşe Başar; Çağlayan, Bora; Henry, Adam Douglas; Prałat, Paweł

2016-01-01

This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals’ access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends. PMID:27701430

Health benefits of primary care social work for adults with complex health and social needs: a systematic review.

PubMed

McGregor, Jules; Mercer, Stewart W; Harris, Fiona M

2018-01-01

The prevalence of complex health and social needs in primary care patients is growing. Furthermore, recent research suggests that the impact of psychosocial distress on the significantly poorer health outcomes in this population may have been underestimated. The potential of social work in primary care settings has been extensively discussed in both health and social work literature and there is evidence that social work interventions in other settings are particularly effective in addressing psychosocial needs. However, the evidence base for specific improved health outcomes related to primary care social work is minimal. This review aimed to identify and synthesise the available evidence on the health benefits of social work interventions in primary care settings. Nine electronic databases were searched from 1990 to 2015 and seven primary research studies were retrieved. Due to the heterogeneity of studies, a narrative synthesis was conducted. Although there is no definitive evidence for effectiveness, results suggest a promising role for primary care social work interventions in improving health outcomes. These include subjective health measures and self-management of long-term conditions, reducing psychosocial morbidity and barriers to treatment and health maintenance. Although few rigorous study designs were found, the contextual detail and clinical settings of studies provide evidence of the practice applicability of social work intervention. Emerging policy on the integration of health and social care may provide an opportunity to develop this model of care. © 2016 John Wiley & Sons Ltd.

Neurobehavioral assessment of maternal odor in developing rat pups: implications for social buffering

PubMed Central

Al Aïn, Syrina; Perry, Rosemarie E.; Nuñez, Bestina; Kayser, Kassandra; Hochman, Chase; Brehman, Elizabeth; LaComb, Miranda; Wilson, Donald A.; Sullivan, Regina M.

2016-01-01

Social support can attenuate the behavioral and stress hormone response to threat, a phenomenon called social buffering. The mother’s social buffering of the infant is one of the more robust examples; yet we understand little about the neurobiology. Using a rodent model, we explore the neurobiology of social buffering by assessing neural processing of the maternal odor, a major cue controlling social buffering in rat pups. We used pups before (postnatal day (PN) 7) and after (PN14, PN23) the functional emergence of social buffering. Pups were injected with 14C 2-deoxyglucose (2-DG) and presented with the maternal odor, a control preferred odor incapable of social buffering (acetophenone), or no odor. Brains were removed, processed for autoradiography and brain areas identified as important in adult social buffering were assessed, including the amygdala basolateral complex (Basolateral Amygdala [BLA]), medial prefrontal cortex (mPFC), and anterior cingulate cortex (ACC). Results suggest dramatic changes in the processing of maternal odor. PN7 pups show mPFC and ACC activation, although PN14 pups showed no activation of the mPFC, ACC, or BLA. All brain areas assessed were recruited by PN23. Additional analysis suggests substantial changes in functional connectivity across development. Together, these results imply complex nonlinear transitions in the neurobiology of social buffering in early life that may provide insight into the changing role of the mother in supporting social buffering. PMID:26934130

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.

Deciphering the crowd: modeling and identification of pedestrian group motion.

PubMed

Yücel, Zeynep; Zanlungo, Francesco; Ikeda, Tetsushi; Miyashita, Takahiro; Hagita, Norihiro

2013-01-14

Associating attributes to pedestrians in a crowd is relevant for various areas like surveillance, customer profiling and service providing. The attributes of interest greatly depend on the application domain and might involve such social relations as friends or family as well as the hierarchy of the group including the leader or subordinates. Nevertheless, the complex social setting inherently complicates this task. We attack this problem by exploiting the small group structures in the crowd. The relations among individuals and their peers within a social group are reliable indicators of social attributes. To that end, this paper identifies social groups based on explicit motion models integrated through a hypothesis testing scheme. We develop two models relating positional and directional relations. A pair of pedestrians is identified as belonging to the same group or not by utilizing the two models in parallel, which defines a compound hypothesis testing scheme. By testing the proposed approach on three datasets with different environmental properties and group characteristics, it is demonstrated that we achieve an identification accuracy of 87% to 99%. The contribution of this study lies in its definition of positional and directional relation models, its description of compound evaluations, and the resolution of ambiguities with our proposed uncertainty measure based on the local and global indicators of group relation.

Deciphering the Crowd: Modeling and Identification of Pedestrian Group Motion

PubMed Central

Yücel, Zeynep; Zanlungo, Francesco; Ikeda, Tetsushi; Miyashita, Takahiro; Hagita, Norihiro

2013-01-01

Associating attributes to pedestrians in a crowd is relevant for various areas like surveillance, customer profiling and service providing. The attributes of interest greatly depend on the application domain and might involve such social relations as friends or family as well as the hierarchy of the group including the leader or subordinates. Nevertheless, the complex social setting inherently complicates this task. We attack this problem by exploiting the small group structures in the crowd. The relations among individuals and their peers within a social group are reliable indicators of social attributes. To that end, this paper identifies social groups based on explicit motion models integrated through a hypothesis testing scheme. We develop two models relating positional and directional relations. A pair of pedestrians is identified as belonging to the same group or not by utilizing the two models in parallel, which defines a compound hypothesis testing scheme. By testing the proposed approach on three datasets with different environmental properties and group characteristics, it is demonstrated that we achieve an identification accuracy of 87% to 99%. The contribution of this study lies in its definition of positional and directional relation models, its description of compound evaluations, and the resolution of ambiguities with our proposed uncertainty measure based on the local and global indicators of group relation. PMID:23344382

Using participatory action research in a community-based initiative addressing complex mental health needs.

PubMed

Knightbridge, Stephen M; King, Robert; Rolfe, Timothy J

2006-04-01

This paper describes the first phase of a larger project that utilizes participatory action research to examine complex mental health needs across an extensive group of stakeholders in the community. Within an objective qualitative analysis of focus group discussions the social ecological model is utilized to explore how integrative activities can be informed, planned and implemented across multiple elements and levels of a system. Seventy-one primary care workers, managers, policy-makers, consumers and carers from across the southern metropolitan and Gippsland regions of Victoria, Australia took part in seven focus groups. All groups responded to an identical set of focusing questions. Participants produced an explanatory model describing the service system, as it relates to people with complex needs, across the levels of social ecological analysis. Qualitative themes analysis identified four priority areas to be addressed in order to improve the system's capacity for working with complexity. These included: (i) system fragmentation; (ii) integrative case management practices; (iii) community attitudes; and (iv) money and resources. The emergent themes provide clues as to how complexity is constructed and interpreted across the system of involved agencies and interest groups. The implications these findings have for the development and evaluation of this community capacity-building project were examined from the perspective of constructing interventions that address both top-down and bottom-up processes.

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

Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) - a case study for Bucharest, Romania

NASA Astrophysics Data System (ADS)

Armaş, I.; Gavriş, A.

2013-06-01

In recent decades, the development of vulnerability frameworks has enlarged the research in the natural hazards field. Despite progress in developing the vulnerability studies, there is more to investigate regarding the quantitative approach and clarification of the conceptual explanation of the social component. At the same time, some disaster-prone areas register limited attention. Among these, Romania's capital city, Bucharest, is the most earthquake-prone capital in Europe and the tenth in the world. The location is used to assess two multi-criteria methods for aggregating complex indicators: the social vulnerability index (SoVI model) and the spatial multi-criteria social vulnerability index (SEVI model). Using the data of the 2002 census we reduce the indicators through a factor analytical approach to create the indices and examine if they bear any resemblance to the known vulnerability of Bucharest city through an exploratory spatial data analysis (ESDA). This is a critical issue that may provide better understanding of the social vulnerability in the city and appropriate information for authorities and stakeholders to consider in their decision making. The study emphasizes that social vulnerability is an urban process that increased in a post-communist Bucharest, raising the concern that the population at risk lacks the capacity to cope with disasters. The assessment of the indices indicates a significant and similar clustering pattern of the census administrative units, with an overlap between the clustering areas affected by high social vulnerability. Our proposed SEVI model suggests adjustment sensitivity, useful in the expert-opinion accuracy.

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.

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...

Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring

PubMed Central

Nigam, Aastha; Dambanemuya, Henry K.; Joshi, Madhav; Chawla, Nitesh V.

2017-01-01

Abstract Peace processes are complex, protracted, and contentious involving significant bargaining and compromising among various societal and political stakeholders. In civil war terminations, it is pertinent to measure the pulse of the nation to ensure that the peace process is responsive to citizens' concerns. Social media yields tremendous power as a tool for dialogue, debate, organization, and mobilization, thereby adding more complexity to the peace process. Using Colombia's final peace agreement and national referendum as a case study, we investigate the influence of two important indicators: intergroup polarization and public sentiment toward the peace process. We present a detailed linguistic analysis to detect intergroup polarization and a predictive model that leverages Tweet structure, content, and user-based features to predict public sentiment toward the Colombian peace process. We demonstrate that had proaccord stakeholders leveraged public opinion from social media, the outcome of the Colombian referendum could have been different. PMID:29235916

Extracurricular Activities in Multiethnic Middle Schools: Ideal Context for Positive Intergroup Attitudes?

PubMed

Knifsend, Casey A; Juvonen, Jaana

2017-06-01

This study examined processes by which extracurricular participation is linked with positive ethnic intergroup attitudes in multiethnic middle schools in California. Specifically, the mediating roles of activity-related cross-ethnic friendships and social identities including alliances with multiple groups were examined in a sample including African American or Black, East or South-East Asian, White, and Latino youth (N = 1,446; M age  = 11.60 in sixth grade). Results of multilevel modeling suggested that in addition to activity-related cross-ethnic friendships, complex social identities mediated the association between availability of cross-ethnic peers in activities and ethnic intergroup attitudes. Results are discussed in terms of how activities can be structured to promote cross-ethnic relationships and complex social identities, as well as positive ethnic intergroup attitudes. © 2016 The Authors. Journal of Research on Adolescence © 2016 Society for Research on Adolescence.

Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring.

PubMed

Nigam, Aastha; Dambanemuya, Henry K; Joshi, Madhav; Chawla, Nitesh V

2017-12-01

Peace processes are complex, protracted, and contentious involving significant bargaining and compromising among various societal and political stakeholders. In civil war terminations, it is pertinent to measure the pulse of the nation to ensure that the peace process is responsive to citizens' concerns. Social media yields tremendous power as a tool for dialogue, debate, organization, and mobilization, thereby adding more complexity to the peace process. Using Colombia's final peace agreement and national referendum as a case study, we investigate the influence of two important indicators: intergroup polarization and public sentiment toward the peace process. We present a detailed linguistic analysis to detect intergroup polarization and a predictive model that leverages Tweet structure, content, and user-based features to predict public sentiment toward the Colombian peace process. We demonstrate that had proaccord stakeholders leveraged public opinion from social media, the outcome of the Colombian referendum could have been different.

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.

Coupled disease-behavior dynamics on complex networks: A review

NASA Astrophysics Data System (ADS)

Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

The Role of Social Identity Complexity in Inter-Group Attitudes among Young Adolescents

ERIC Educational Resources Information Center

Knifsend, Casey A.; Juvonen, Jaana

2013-01-01

To supplement research on adolescent social identities, the current study examined how social identity complexity relates to ethnic inter-group attitudes in a young adolescent sample (N = 97; "age range" = 12-14 years). Social identity complexity refers to the perceived overlap of groups with which youth align themselves. Descriptive…

Social Identity Complexity, Cross-Ethnic Friendships, and Intergroup Attitudes in Urban Middle Schools

ERIC Educational Resources Information Center

Knifsend, Casey A.; Juvonen, Jaana

2014-01-01

This study investigated contextual antecedents (i.e., cross-ethnic peers and friends) and correlates (i.e., intergroup attitudes) of social identity complexity in seventh grade. Social identity complexity refers to the perceived overlap among social groups with which youth identify. Identifying mostly with out-of-school sports, religious…

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

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…

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…

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

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.

The Social Identity Model of Cessation Maintenance: formulation and initial evidence.

PubMed

Frings, Daniel; Albery, Ian P

2015-05-01

Group therapy can be highly influential in helping addicts (individuals presenting with problematic addictive behaviors) achieve and maintain cessation. The efficacy of such groups can be understood by the effects they have on members' social identity and also through associated group processes. The current paper introduces the Social Identity Model of Cessation Maintenance (SIMCM). The SIMCM outlines how a number of processes (including self/collective efficacy and esteem, normative structure and social support and control) may affect cessation maintenance. It also provides a framework to make predictions about how automatic and/or implicit processes influence the activation of addiction relevant identities through cognitive accessibility and complexity in particular. A review of initial empirical evidence supporting some of the key specified relationships is provided, along with potential applications in therapy settings. Insights into how SIMCM could be generalized beyond treatment contexts and avenues for future research are outlined. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Brain and Social Networks: Fundamental Building Blocks of Human Experience.

PubMed

Falk, Emily B; Bassett, Danielle S

2017-09-01

How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. 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.

[Social determinants of odontalgia in epidemiological studies: theoretical review and proposed conceptual model].

PubMed

Bastos, João Luiz Dornelles; Gigante, Denise Petrucci; Peres, Karen Glazer; Nedel, Fúlvio Borges

2007-01-01

The epidemiological literature has been limited by the absence of a theoretical framework reflecting the complexity of causal mechanisms for the occurrence of health phenomena / disease conditions. In the field of oral epidemiology, such lack of theory also prevails, since dental caries the leading topic in oral research has been often studied through a biological and reductionist viewpoint. One of the most important consequences of dental caries is dental pain (odontalgia), which has received little attention in studies with sophisticated theoretical models and powerful designs to establish causal relationships. The purpose of this study is to review the scientific literature on the determinants of odontalgia and to discuss theories proposed for the explanation of the phenomenon. Conceptual models and emerging theories on the social determinants of oral health are revised, in an attempt to build up links with the bio-psychosocial pain model, proposing a more elaborate causal model for odontalgia. The framework suggests causal pathways between social structure and oral health through material, psychosocial and behavioral pathways. Aspects of the social structure are highlighted in order to relate them to odontalgia, stressing their importance in discussions of causal relationships in oral health research.

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

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.

Direct and indirect relationships between physical activity and happiness levels among older adults: a cross-sectional study.

PubMed

de Souto Barreto, Philipe

2014-09-01

The purposes of this study were to examine if physical activity (PA) is associated to happiness and to investigate if social functioning and health status mediate this association. Participants of this cross-sectional study were 323 men and women, age 60 or over, who were covered by the medical insurance of the French National Education System, France. They received by mail a self-report questionnaire that asked for information about general health, PA, and happiness. In multinomial logistic regressions, the total volume of PA was associated to higher levels of happiness, but this association disappeared in the presence of social functioning. A structural equation modelling (SEM) showed an indirect association between PA and happiness, which was mediated by participants' health status and social functioning; in this SEM model, social functioning was the only variable directly associated to happiness. Complex associations among PA, health status, and social functioning appear to determine happiness levels in older adults.

Social learning: medical student perceptions of geriatric house calls.

PubMed

Abbey, Linda; Willett, Rita; Selby-Penczak, Rachel; McKnight, Roberta

2010-01-01

Bandura's social learning theory provides a useful conceptual framework to understand medical students' perceptions of a house calls experience at Virginia Commonwealth University School of Medicine. Social learning and role modeling reflect Liaison Committee on Medical Education guidelines for "Medical schools (to) ensure that the learning environment for medical students promotes the development of explicit and appropriate professional attributes (attitudes, behaviors, and identity) in their medical students." This qualitative study reports findings from open-ended survey questions from 123 medical students who observed a preceptor during house calls to elderly homebound patients. Their comments included reflections on the medical treatment as well as interactions with family and professional care providers. Student insights about the social learning process they experienced during house calls to geriatric patients characterized physician role models as dedicated, compassionate, and communicative. They also described patient care in the home environment as comprehensive, personalized, more relaxed, and comfortable. Student perceptions reflect an appreciation of the richness and complexity of details learned from home visits and social interaction with patients, families, and caregivers.

Spreading of healthy mood in adolescent social networks

PubMed Central

Hill, E. M.; Griffiths, F. E.; House, T.

2015-01-01

Depression is a major public health concern worldwide. There is evidence that social support and befriending influence mental health, and an improved understanding of the social processes that drive depression has the potential to bring significant public health benefits. We investigate transmission of mood on a social network of adolescents, allowing flexibility in our model by making no prior assumption as to whether it is low mood or healthy mood that spreads. Here, we show that while depression does not spread, healthy mood among friends is associated with significantly reduced risk of developing and increased chance of recovering from depression. We found that this spreading of healthy mood can be captured using a non-linear complex contagion model. Having sufficient friends with healthy mood can halve the probability of developing, or double the probability of recovering from, depression over a 6–12-month period on an adolescent social network. Our results suggest that promotion of friendship between adolescents can reduce both incidence and prevalence of depression. PMID:26290075

Spreading of healthy mood in adolescent social networks.

PubMed

Hill, E M; Griffiths, F E; House, T

2015-08-22

Depression is a major public health concern worldwide. There is evidence that social support and befriending influence mental health, and an improved understanding of the social processes that drive depression has the potential to bring significant public health benefits. We investigate transmission of mood on a social network of adolescents, allowing flexibility in our model by making no prior assumption as to whether it is low mood or healthy mood that spreads. Here, we show that while depression does not spread, healthy mood among friends is associated with significantly reduced risk of developing and increased chance of recovering from depression. We found that this spreading of healthy mood can be captured using a non-linear complex contagion model. Having sufficient friends with healthy mood can halve the probability of developing, or double the probability of recovering from, depression over a 6-12-month period on an adolescent social network. Our results suggest that promotion of friendship between adolescents can reduce both incidence and prevalence of depression. © 2015 The Authors.

The formation of novel social category conjunctions in working memory: A possible role for the episodic buffer?

PubMed

Hutter, Russell R C; Allen, Richard J; Wood, Chantelle

2016-01-01

Recent research (e.g., Hutter, Crisp, Humphreys, Waters, & Moffit; Siebler) has confirmed that combining novel social categories involves two stages (e.g., Hampton; Hastie, Schroeder, & Weber). Furthermore, it is also evident that following stage 1 (constituent additivity), the second stage in these models involves cognitively effortful complex reasoning. However, while current theory and research has addressed how category conjunctions are initially represented to some degree, it is not clear precisely where we first combine or bind existing social constituent categories. For example, how and where do we compose and temporarily store a coherent representation of an individual who shares membership of "female" and "blacksmith" categories? In this article, we consider how the revised multi-component model of working memory (Baddeley) can assist in resolving the representational limitations in the extant two-stage theoretical models. This is a new approach to understanding how novel conjunctions form new bound "composite" representations.

Developing a model of adolescent friendship formation on the internet.

PubMed

Peter, Jochen; Valkenburg, Patti M; Schouten, Alexander P

2005-10-01

Previous research has been largely silent about what precisely influences online friendship formation and has ignored motives for online communication as potential explanations. Drawing on a sample of 493 adolescents, this study tested a path model of adolescent friendship formation including as predictors introversion/extraversion, online self-disclosure, motive for social compensation, and frequency of online communication. Our path analysis showed that extraverted adolescents self-disclosed and communicated online more frequently, which, in turn, facilitated the formation of online friendships. Introverted adolescents, by contrast, were more strongly motivated to communicate online to compensate for lacking social skills. This increased their chances of making friends online. Among introverted adolescents, a stronger motive for social compensation also led to more frequent online communication and online self-disclosure, resulting in more online friendships. The model suggests that the antecedents of online friendship formation are more complex than previously assumed and that motives for online communication should be studied more closely.

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.

Fundamental structures of dynamic social networks.

PubMed

Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

2016-09-06

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.

Fundamental structures of dynamic social networks

PubMed Central

Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

2016-01-01

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision. PMID:27555584

Radical behaviorist interpretation: Generating and evaluating an account of consumer behavior.

PubMed

Foxall, G R

1998-01-01

This article considers an approach to the radical behaviorist interpretation of complex human social behavior. The chosen context is consumer psychology, a field currently dominated by cognitive models of purchase and consumption. The nature of operant interpretation is considered, and several levels of operant analysis of complex economic behavior in affluent marketing-oriented economies are developed. Empirical evidence for the interpretation is considered, and a case is made for the qualified use of the hypothetico-deductive method in the appraisal of operant interpretations of complex behaviors.

Radical behaviorist interpretation: Generating and evaluating an account of consumer behavior

PubMed Central

Foxall, Gordon R.

1998-01-01

This article considers an approach to the radical behaviorist interpretation of complex human social behavior. The chosen context is consumer psychology, a field currently dominated by cognitive models of purchase and consumption. The nature of operant interpretation is considered, and several levels of operant analysis of complex economic behavior in affluent marketing-oriented economies are developed. Empirical evidence for the interpretation is considered, and a case is made for the qualified use of the hypothetico-deductive method in the appraisal of operant interpretations of complex behaviors. PMID:22478315

The Emerging Field of Human Social Genomics

PubMed Central

Slavich, George M.; Cole, Steven W.

2013-01-01

Although we generally experience our bodies as being biologically stable across time and situations, an emerging field of research is demonstrating that external social conditions, especially our subjective perceptions of those conditions, can influence our most basic internal biological processes—namely, the expression of our genes. This research on human social genomics has begun to identify the types of genes that are subject to social-environmental regulation, the neural and molecular mechanisms that mediate the effects of social processes on gene expression, and the genetic polymorphisms that moderate individual differences in genomic sensitivity to social context. The molecular models resulting from this research provide new opportunities for understanding how social and genetic factors interact to shape complex behavioral phenotypes and susceptibility to disease. This research also sheds new light on the evolution of the human genome and challenges the fundamental belief that our molecular makeup is relatively stable and impermeable to social-environmental influence. PMID:23853742

Aging and social networks in Spain: the importance of pubs and churches.

PubMed

Buz, José; Sanchez, Marta; Levenson, Michael R; Aldwin, Carolyn M

2014-01-01

We examined whether the social convoy model and socioemotional selectivity theory apply in collectivistic cultures by examining the contextual factors which are hypothesized to mediate age-related differences in social support in a collectivist European country. Five hundred Spanish community-dwelling older adults (Mean age = 74.78, SD = 7.76, range = 60-93) were interviewed to examine structural aspects of their social networks. We found that age showed highly complex relationships with network size and frequency of interaction, depending on the network circle and the mediation of cultural factors. Family structure was important for social relations in the inner circle, while pubs and churches were important for peripheral relations. Surprisingly, pub attendance was the most important variable for maintenance of social support of peripheral network members. In general, the results support the applicability of the social convoy and socioemotional selectivity constructs to social support among Spanish older adults.

Processing of social and monetary rewards in the human striatum.

PubMed

Izuma, Keise; Saito, Daisuke N; Sadato, Norihiro

2008-04-24

Despite an increasing focus on the neural basis of human decision making in neuroscience, relatively little attention has been paid to decision making in social settings. Moreover, although human social decision making has been explored in a social psychology context, few neural explanations for the observed findings have been considered. To bridge this gap and improve models of human social decision making, we investigated whether acquiring a good reputation, which is an important incentive in human social behaviors, activates the same reward circuitry as monetary rewards. In total, 19 subjects participated in functional magnetic resonance imaging (fMRI) experiments involving monetary and social rewards. The acquisition of one's good reputation robustly activated reward-related brain areas, notably the striatum, and these overlapped with the areas activated by monetary rewards. Our findings support the idea of a "common neural currency" for rewards and represent an important first step toward a neural explanation for complex human social behaviors.

The role of prediction in social neuroscience

PubMed Central

Brown, Elliot C.; Brüne, Martin

2012-01-01

Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e., by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representations have been found when experiencing one's own and observing other's actions, rewards, errors, and emotions such as fear and pain. These general principles of the “predictive brain” are well established and have already begun to be applied to social aspects of cognition. The application and relevance of these predictive principles to social cognition are discussed in this article. Evidence is presented to argue that simple non-social cognitive processes can be extended to explain complex cognitive processes required for social interaction, with common neural activity seen for both social and non-social cognitions. A number of studies are included which demonstrate that bottom-up sensory input and top-down expectancies can be modulated by social information. The concept of competing social forward models and a partially distinct category of social prediction errors are introduced. The evolutionary implications of a “social predictive brain” are also mentioned, along with the implications on psychopathology. The review presents a number of testable hypotheses and novel comparisons that aim to stimulate further discussion and integration between currently disparate fields of research, with regard to computational models, behavioral and neurophysiological data. This promotes a relatively new platform for inquiry in social neuroscience with implications in social learning, theory of mind, empathy, the evolution of the social brain, and potential strategies for treating social cognitive deficits. PMID:22654749

Animal Models of Depression: Molecular Perspectives

PubMed Central

Krishnan, Vaishnav; Nestler, Eric J.

2012-01-01

Much of the current understanding about the pathogenesis of altered mood, impaired concentration and neurovegetative symptoms in major depression has come from animal models. However, because of the unique and complex features of human depression, the generation of valid and insightful depression models has been less straightforward than modeling other disabling diseases like cancer or autoimmune conditions. Today’s popular depression models creatively merge ethologically valid behavioral assays with the latest technological advances in molecular biology and automated video-tracking. This chapter reviews depression assays involving acute stress (e.g., forced swim test), models consisting of prolonged physical or social stress (e.g., social defeat), models of secondary depression, genetic models, and experiments designed to elucidate the mechanisms of antidepressant action. These paradigms are critically evaluated in relation to their ease, validity and replicability, the molecular insights that they have provided, and their capacity to offer the next generation of therapeutics for depression. PMID:21225412

Prefrontal Cortex and Social Cognition in Mouse and Man

PubMed Central

Bicks, Lucy K.; Koike, Hiroyuki; Akbarian, Schahram; Morishita, Hirofumi

2015-01-01

Social cognition is a complex process that requires the integration of a wide variety of behaviors, including salience, reward-seeking, motivation, knowledge of self and others, and flexibly adjusting behavior in social groups. Not surprisingly, social cognition represents a sensitive domain commonly disrupted in the pathology of a variety of psychiatric disorders including Autism Spectrum Disorder (ASD) and Schizophrenia (SCZ). Here, we discuss convergent research from animal models to human disease that implicates the prefrontal cortex (PFC) as a key regulator in social cognition, suggesting that disruptions in prefrontal microcircuitry play an essential role in the pathophysiology of psychiatric disorders with shared social deficits. We take a translational perspective of social cognition, and review three key behaviors that are essential to normal social processing in rodents and humans, including social motivation, social recognition, and dominance hierarchy. A shared prefrontal circuitry may underlie these behaviors. Social cognition deficits in animal models of neurodevelopmental disorders like ASD and SCZ have been linked to an altered balance of excitation and inhibition (E/I ratio) within the cortex generally, and PFC specifically. A clear picture of the mechanisms by which altered E/I ratio in the PFC might lead to disruptions of social cognition across a variety of behaviors is not well understood. Future studies should explore how disrupted developmental trajectory of prefrontal microcircuitry could lead to altered E/I balance and subsequent deficits in the social domain. PMID:26635701

“Speaking the Dialect”: Understanding Public Discourse in the Aftermath of an HIV Vaccine Trial Shutdown

PubMed Central

Logie, Carmen; James, LLana; Charles, Tamicka; Maxwell, John; Salam, Khaled; Woodford, Michael

2011-01-01

Objectives. We investigated how persons from key populations at higher risk of HIV exposure interpreted the process and outcomes of the Step Study HIV-1 vaccine trial, which was terminated early, and implications for willingness to participate in and community support for HIV vaccine research. Methods. We used qualitative methods and a community-based approach in 9 focus groups (n = 72) among ethnically and sexually diverse populations and 6 semistructured key informant interviews in Ontario, Canada, in 2007 to 2008. Results. Participants construed social meaning from complex clinical and biomedical phenomena. Social representations and mental models emerged in fears of vaccine-induced infection, conceptualizations of unfair recruitment practices and increased risk behaviors among trial participants, and questioning of informed consent. Narratives of altruism and the common good demonstrated support for future trials. Conclusions. Public discourse on HIV vaccine trials is a productive means of interpreting complex clinical trial processes and outcomes in the context of existing beliefs and experiences regarding HIV vaccines, medical research, and historical disenfranchisement. Strategic engagement with social representations and mental models may promote meaningful community involvement in biomedical HIV prevention research. PMID:21778490

Resting state brain networks in the prairie vole.

PubMed

Ortiz, Juan J; Portillo, Wendy; Paredes, Raul G; Young, Larry J; Alcauter, Sarael

2018-01-19

Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

A 3-states magnetic model of binary decisions in sociophysics

NASA Astrophysics Data System (ADS)

Fernandez, Miguel A.; Korutcheva, Elka; de la Rubia, F. Javier

2016-11-01

We study a diluted Blume-Capel model of 3-states sites as an attempt to understand how some social processes as cooperation or organization happen. For this aim, we study the effect of the complex network topology on the equilibrium properties of the model, by focusing on three different substrates: random graph, Watts-Strogatz and Newman substrates. Our computer simulations are in good agreement with the corresponding analytical results.

A two-stage broadcast message propagation model in social networks

NASA Astrophysics Data System (ADS)

Wang, Dan; Cheng, Shun-Jun

2016-11-01

Message propagation in social networks is becoming a popular topic in complex networks. One of the message types in social networks is called broadcast message. It refers to a type of message which has a unique and unknown destination for the publisher, such as 'lost and found'. Its propagation always has two stages. Due to this feature, rumor propagation model and epidemic propagation model have difficulty in describing this message's propagation accurately. In this paper, an improved two-stage susceptible-infected-removed model is proposed. We come up with the concept of the first forwarding probability and the second forwarding probability. Another part of our work is figuring out the influence to the successful message transmission chance in each level resulting from multiple reasons, including the topology of the network, the receiving probability, the first stage forwarding probability, the second stage forwarding probability as well as the length of the shortest path between the publisher and the relevant destination. The proposed model has been simulated on real networks and the results proved the model's effectiveness.

Perceived control moderates the relationship between social capital and binge drinking: longitudinal findings from the Montreal Neighborhood Networks and Health Aging (MoNNET-HA) panel.

PubMed

Child, Stephanie; Stewart, Steven; Moore, Spencer

2017-02-01

Cross-sectional research suggests social capital has negative consequences for problem drinking behaviors. Previous studies have suggested psychosocial resources, including perceived control, may buffer this association. Little research has examined whether such relationships persist longitudinally. Random effects models examined between-person relationships among problem drinking, social capital, and perceived control, and whether perceived control moderated the relationship between social capital and drinking. Fixed effects models assessed whether social capital and perceived control were related to changes in problem drinking. Greater network capital and generalized trust predicted higher odds of binge drinking (RR = 1.08; 95% CI = 1.03-1.12 and RR = 1.23; 95% CI = 1.03-1.48, respectively). Perceived control moderated the positive association of network capital with binge drinking (RR = 0.91; 95% CI = 0.87-0.96). The present findings support previous notions about the complex role of social capital on health, and offer new insights on the role of perceived control on problem drinking. Copyright © 2016 Elsevier Inc. All rights reserved.

Object-directed imitation in autism spectrum disorder is differentially influenced by motoric task complexity, but not social contextual cues.

PubMed

Chetcuti, Lacey; Hudry, Kristelle; Grant, Megan; Vivanti, Giacomo

2017-11-01

We examined the role of social motivation and motor execution factors in object-directed imitation difficulties in autism spectrum disorder. A series of to-be-imitated actions was presented to 35 children with autism spectrum disorder and 20 typically developing children on an Apple ® iPad ® by a socially responsive or aloof model, under conditions of low and high motor demand. There were no differences in imitation performance (i.e. the number of actions reproduced within a fixed sequence), for either group, in response to a model who acted socially responsive or aloof. Children with autism spectrum disorder imitated the high motor demand task more poorly than the low motor demand task, while imitation performance for typically developing children was equivalent across the low and high motor demand conditions. Furthermore, imitative performance in the autism spectrum disorder group was unrelated to social reciprocity, though positively associated with fine motor coordination. These results suggest that difficulties in object-directed imitation in autism spectrum disorder are the result of motor execution difficulties, not reduced social motivation.

Effects of a community health promotion program on social factors in a vulnerable older adult population residing in social housing.

PubMed

Agarwal, Gina; Brydges, Madison

2018-04-16

Supporting older adults' health and wellbeing in the community is an important policy goal that can be supported by health promotion. Despite widespread acceptance of the biopsychosocial model of health and its relation to health, many health promotion programs fail to realize this model in program design. Further, there is limited evidence to support program design targeting social determinants of health such as social isolation or connectedness. To fill this gap, we aimed to understand older adult's experiences participating in cardiovascular health promotion program in a subsidized residential building to capture unintended 'spin-off' psychosocial effects. This study took a constructivist, ethnographic approach utilizing participant observation and semi-structured interviews with participants of the program to understand participant's lived experiences of a health promotion program. In total, we conducted eighty hours of field work and fifteen semi-structured interviews with participants of the program. Thematic analysis was used to analyze the data. Four themes emerged. First, the health promotion program filled a perceived gap caused by a constrained and impersonal health care system. Secondly, the program connected older adults with resources and provided regular and secure access to health information and support. Third, for some residents, the program facilitated social relationships between older adults, leaving participants feeling more socially connected to other residents. Lastly, a paradox of loneliness emerged where older adults talked openly about feelings of loneliness, however not in relation to themselves, but rather regarding their peers. Psychosocial aspects of health, such as loneliness, social connectedness, and social support may be of equal value as the physical health benefits to the older adults who participate in health promotion programs. Incorporating these elements into programming is a complex goal, and the complexity of targeting social determinants of health such as social loneliness or connectedness should not be under-estimated. Given the benefits of targeting social determinants of health, future research should be considered that measure both the objective and subjective aspects of social isolation, loneliness and connectedness in health promotion programming.

Information Retrieval and Graph Analysis Approaches for Book Recommendation.

PubMed

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

Information Retrieval and Graph Analysis Approaches for Book Recommendation

PubMed Central

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments. PMID:26504899

Rumor spreading model with noise interference in complex social networks

NASA Astrophysics Data System (ADS)

Zhu, Liang; Wang, Youguo

2017-03-01

In this paper, a modified susceptible-infected-removed (SIR) model has been proposed to explore rumor diffusion on complex social networks. We take variation of connectivity into consideration and assume the variation as noise. On the basis of related literature on virus networks, the noise is described as standard Brownian motion while stochastic differential equations (SDE) have been derived to characterize dynamics of rumor diffusion both on homogeneous networks and heterogeneous networks. Then, theoretical analysis on homogeneous networks has been demonstrated to investigate the solution of SDE model and the steady state of rumor diffusion. Simulations both on Barabási-Albert (BA) network and Watts-Strogatz (WS) network display that the addition of noise accelerates rumor diffusion and expands diffusion size, meanwhile, the spreading speed on BA network is much faster than on WS network under the same noise intensity. In addition, there exists a rumor diffusion threshold in statistical average meaning on homogeneous network which is absent on heterogeneous network. Finally, we find a positive correlation between peak value of infected individuals and noise intensity while a negative correlation between rumor lifecycle and noise intensity overall.

More than mere numbers: the impact of lethal control on the social stability of a top-order predator.

PubMed

Wallach, Arian D; Ritchie, Euan G; Read, John; O'Neill, Adam J

2009-09-02

Population control of socially complex species may have profound ecological implications that remain largely invisible if only their abundance is considered. Here we discuss the effects of control on a socially complex top-order predator, the dingo (Canis lupus dingo). Since European occupation of Australia, dingoes have been controlled over much of the continent. Our aim was to investigate the effects of control on their abundance and social stability. We hypothesized that dingo abundance and social stability are not linearly related, and proposed a theoretical model in which dingo populations may fluctuate between three main states: (A) below carrying capacity and socially fractured, (B) above carrying capacity and socially fractured, or (C) at carrying capacity and socially stable. We predicted that lethal control would drive dingoes into the unstable states A or B, and that relaxation of control would allow recovery towards C. We tested our predictions by surveying relative abundance (track density) and indicators of social stability (scent-marking and howling) at seven sites in the arid zone subject to differing degrees of control. We also monitored changes in dingo abundance and social stability following relaxation and intensification of control. Sites where dingoes had been controlled within the previous two years were characterized by low scent-marking activity, but abundance was similar at sites with and without control. Signs of social stability steadily increased the longer an area was allowed to recover from control, but change in abundance did not follow a consistent path. Comparison of abundance and stability among all sites and years demonstrated that control severely fractures social groups, but that the effect of control on abundance was neither consistent nor predictable. Management decisions involving large social predators must therefore consider social stability to ensure their conservation and ecological functioning.

Using cognitive work analysis to explore activity allocation within military domains.

PubMed

Jenkins, D P; Stanton, N A; Salmon, P M; Walker, G H; Young, M S

2008-06-01

Cognitive work analysis (CWA) is frequently advocated as an approach for the analysis of complex socio-technical systems. Much of the current CWA literature within the military domain pays particular attention to its initial phases; work domain analysis and contextual task analysis. Comparably, the analysis of the social and organisational constraints receives much less attention. Through the study of a helicopter mission planning system software tool, this paper describes an approach for investigating the constraints affecting the distribution of work. The paper uses this model to evaluate the potential benefits of the social and organisational analysis phase within a military context. The analysis shows that, through its focus on constraints, the approach provides a unique description of the factors influencing the social organisation within a complex domain. This approach appears to be compatible with existing approaches and serves as a validation of more established social analysis techniques. As part of the ergonomic design of mission planning systems, the social organisation and cooperation analysis phase of CWA provides a constraint-based description informing allocation of function between key actor groups. This approach is useful because it poses questions related to the transfer of information and optimum working practices.

The treatment of parental height as a biological factor in studies of birth weight and childhood growth

PubMed Central

Spencer, N; Logan, S

2002-01-01

Parental height is frequently treated as a biological variable in studies of birth weight and childhood growth. Elimination of social variables from multivariate models including parental height as a biological variable leads researchers to conclude that social factors have no independent effect on the outcome. This paper challenges the treatment of parental height as a biological variable, drawing on extensive evidence for the determination of adult height through a complex interaction of genetic and social factors. The paper firstly seeks to establish the importance of social factors in the determination of height. The methodological problems associated with treatment of parental height as a purely biological variable are then discussed, illustrated by data from published studies and by analysis of data from the 1958 National Childhood Development Study (NCDS). The paper concludes that a framework for studying pathways to pregnancy and childhood outcomes needs to take account of the complexity of the relation between genetic and social factors and be able to account for the effects of multiple risk factors acting cumulatively across time and across generations. Illustrations of these approaches are given using NCDS data. PMID:12193422

Social Behavior of Offspring Following Prenatal Cocaine Exposure in Rodents: A Comparison with Prenatal Alcohol

PubMed Central

Sobrian, Sonya K.; Holson, R. R.

2011-01-01

Clinical and experimental reports suggest that prenatal cocaine exposure (PCE) alters the offsprings’ social interactions with caregivers and conspecifics. Children exposed to prenatal cocaine show deficits in caregiver attachment and play behavior. In animal models, a developmental pattern of effects that range from deficits in play and social interaction during adolescence, to aggressive reactions during competition in adulthood is seen. This review will focus primarily on the effects of PCE on social behaviors involving conspecifics in animal models. Social relationships are critical to the developing organism; maternally directed interactions are necessary for initial survival. Juvenile rats deprived of play behavior, one of the earliest forms of non-mother directed social behaviors in rodents, show deficits in learning tasks and sexual competence. Social behavior is inherently complex. Because the emergence of appropriate social skills involves the interplay between various conceptual and biological facets of behavior and social information, it may be a particularly sensitive measure of prenatal insult. The social behavior surveyed include social interactions, play behavior/fighting, scent marking, and aggressive behavior in the offspring, as well as aspects of maternal behavior. The goal is to determine if there is a consensus of results in the literature with respect to PCE and social behaviors, and to discuss discrepant findings in terms of exposure models, the paradigms, and dependent variables, as well as housing conditions, and the sex and age of the offspring at testing. As there is increasing evidence that deficits in social behavior may be sequelae of developmental exposure alcohol, we compare changes in social behaviors reported for prenatal alcohol with those reported for prenatal cocaine. Shortcomings in the both literatures are identified and addressed in an effort to improve the translational value of future experimentation. PMID:22144967

Modelling Levels of Collaboration Among Health and Social Care Professionals in the Management of a Mental Health Plan.

PubMed

Luzi, Daniela; Pecoraro, Fabrizio; Tamburis, Oscar

2018-01-01

Professional collaboration among health and social care providers is considered an essential pattern to improve the integration of care. This is particularly important considering the planning activities for children with complex conditions. In this paper the level of collaboration among professionals in the development and implementation of the personalized plan in the mental health domain is analysed across 30 EU/EEA countries within the MOCHA project.

Infrastructure Tsunami Could Easily Dwarf Climate Change

NASA Astrophysics Data System (ADS)

Lansing, Stephen

Compared to the physical and biological sciences, so far complexity has had far less impact on mainstream social science. This is not surprising, but it is alarming because we find ourselves in the midst of a planetary-scale transition from the Holocene to the Anthropocene. We have already breached some planetary boundaries for sustainability, but those tipping points are nearly invisible from the perspective of the linear equilibrium models that continue to hold sway in social science...

Physiology and biochemistry of honey bees

USDA-ARS?s Scientific Manuscript database

Despite their tremendous economic importance, honey bees are not a typical model system for studying general questions of insect physiology. This is primarily due to the fact that honey bees live in complex social settings which impact their physiological and biochemical characteristics. Not surpris...

Development of Civic Engagement: Theoretical and Methodological Issues

ERIC Educational Resources Information Center

Lerner, Richard M.; Wang, Jun; Champine, Robey B.; Warren, Daniel J. A.; Erickson, Karl

2014-01-01

Within contemporary developmental science, models derived from relational developmental systems (RDS) metatheory emphasize that the basic process of human development involves mutually-influential relations, termed developmental regulations, between the developing individual and his or her complex and changing physical, social, and cultural…

Non-parametric causality detection: An application to social media and financial data

NASA Astrophysics Data System (ADS)

Tsapeli, Fani; Musolesi, Mirco; Tino, Peter

2017-10-01

According to behavioral finance, stock market returns are influenced by emotional, social and psychological factors. Several recent works support this theory by providing evidence of correlation between stock market prices and collective sentiment indexes measured using social media data. However, a pure correlation analysis is not sufficient to prove that stock market returns are influenced by such emotional factors since both stock market prices and collective sentiment may be driven by a third unmeasured factor. Controlling for factors that could influence the study by applying multivariate regression models is challenging given the complexity of stock market data. False assumptions about the linearity or non-linearity of the model and inaccuracies on model specification may result in misleading conclusions. In this work, we propose a novel framework for causal inference that does not require any assumption about a particular parametric form of the model expressing statistical relationships among the variables of the study and can effectively control a large number of observed factors. We apply our method in order to estimate the causal impact that information posted in social media may have on stock market returns of four big companies. Our results indicate that social media data not only correlate with stock market returns but also influence them.

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

PubMed

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

The Norrtaelje model: a unique model for integrated health and social care in Sweden.

PubMed

Bäck, Monica Andersson; Calltorp, Johan

2015-01-01

Many countries organise and fund health and social care separately. The Norrtaelje model is a Swedish initiative that transformed the funding and organisation of health and social care in order to better integrate care for older people with complex needs. In Norrtaelje model, this transformation made it possible to bringing the team together, to transfer responsibility to different providers, to use care coordinators, and to develop integrated pathways and plans around transitions in and out of hospital and from nursing homes to hospital. The Norrtaelje model operates in the context of the Swedish commitment to universal coverage and public programmes based on tax-funded resources that are pooled and redistributed to citizens on the basis of need. The experience of Norrtaelje model suggests that one way to promote integration of health and social care is to start with a transformation that aligns these two sectors in terms of high level organisation and funding. This transformation then enables the changes in operations and management that can be translated into changes in care delivery. This "top-down" approach must be in-line with national priorities and policies but ultimately is successful only if the culture, resource allocation and management are changed throughout the local system.

Social networks as embedded complex adaptive systems.

PubMed

Benham-Hutchins, Marge; Clancy, Thomas R

2010-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

Training versus engagement as paths to cognitive enrichment with aging.

PubMed

Stine-Morrow, Elizabeth A L; Payne, Brennan R; Roberts, Brent W; Kramer, Arthur F; Morrow, Daniel G; Payne, Laura; Hill, Patrick L; Jackson, Joshua J; Gao, Xuefei; Noh, Soo Rim; Janke, Megan C; Parisi, Jeanine M

2014-12-01

While a training model of cognitive intervention targets the improvement of particular skills through instruction and practice, an engagement model is based on the idea that being embedded in an intellectually and socially complex environment can impact cognition, perhaps even broadly, without explicit instruction. We contrasted these 2 models of cognitive enrichment by randomly assigning healthy older adults to a home-based inductive reasoning training program, a team-based competitive program in creative problem solving, or a wait-list control. As predicted, those in the training condition showed selective improvement in inductive reasoning. Those in the engagement condition, on the other hand, showed selective improvement in divergent thinking, a key ability exercised in creative problem solving. On average, then, both groups appeared to show ability-specific effects. However, moderators of change differed somewhat for those in the engagement and training interventions. Generally, those who started either intervention with a more positive cognitive profile showed more cognitive growth, suggesting that cognitive resources enabled individuals to take advantage of environmental enrichment. Only in the engagement condition did initial levels of openness and social network size moderate intervention effects on cognition, suggesting that comfort with novelty and an ability to manage social resources may be additional factors contributing to the capacity to take advantage of the environmental complexity associated with engagement. Collectively, these findings suggest that training and engagement models may offer alternative routes to cognitive resilience in late life. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Training versus Engagement as Paths to Cognitive Enrichment with Aging

PubMed Central

Stine-Morrow, Elizabeth A. L.; Payne, Brennan R.; Roberts, Brent W.; Kramer, Arthur F.; Morrow, Daniel G.; Payne, Laura; Hill, Patrick L.; Jackson, Joshua J.; Gao, Xuefei; Noh, Soo Rim; Janke, Megan C.; Parisi, Jeanine M.

2015-01-01

While a training model of cognitive intervention targets the improvement of particular skills through instruction and practice, an engagement model is based on the idea that being embedded in an intellectually and socially complex environment can impact cognition, perhaps even broadly, without explicit instruction. We contrasted these two models of cognitive enrichment by randomly assigning healthy older adults to a home-based inductive reasoning training program, a team-based competitive program in creative problem solving, or to a wait-list control. As predicted, those in the training condition showed selective improvement in inductive reasoning. Those in the engagement condition, on the other hand, showed selective improvement in divergent thinking, a key ability exercised in creative problem solving. On average, then, both groups appeared to show ability-specific effects. However, moderators of change differed somewhat for those in the engagement and training interventions. Generally, those who started either intervention with a more positive cognitive profile showed more cognitive growth, suggesting that cognitive resources enabled individuals to take advantage of environmental enrichment. Only in the engagement condition did initial levels of openness and social network size moderate intervention effects on cognition, suggesting that comfort with novelty and an ability to manage social resources may be additional factors contributing to the capacity to take advantage of the environmental complexity associated with engagement. Collectively, these findings suggest that training and engagement models may offer alternative routes to cognitive resilience in late life. PMID:25402337

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 dual change model of life satisfaction and functioning for individuals with schizophrenia

PubMed Central

Edmondson, Melissa; Pahwa, Rohini; Lee, Karen Kyeunghae; Hoe, Maanse; Brekke, John S.

2013-01-01

Despite the notion that increases in functioning should be associated with increases in life satisfaction in schizophrenia, research has often found no association between the two. Dual change models of global and domain-specific life satisfaction and functioning were examined in 145 individuals with schizophrenia receiving community-based services over 12 months. Functioning and satisfaction were measured using the Role Functioning Scale and Satisfaction with Life Scale. Data were analyzed using latent growth curve modeling. Improvement in global life satisfaction was associated with improvement in overall functioning over time. Satisfaction with living situation also improved as independent functioning improved. Work satisfaction did not improve as work functioning improved. Although social functioning improved, satisfaction with social relationships did not. The link between overall functioning and global life satisfaction provides support for a recovery-based orientation to community based psychosocial rehabilitation services. When examining sub-domains, the link between outcomes and subjective experience suggests a more complex picture than previously found. These findings are crucial to interventions and programs aimed at improving functioning and the subjective experiences of consumers recovering from mental illness. Interventions that show improvements in functional outcomes can assume that they will show concurrent improvements in global life satisfaction as well and in satisfaction with independent living. Interventions geared toward improving social functioning will need to consider the complexity of social relationships and how they affect satisfaction associated with personal relationships. Interventions geared towards improving work functioning will need to consider how the quality and level of work affect satisfaction with employment. PMID:22591780

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.

Quantifying the propagation of distress and mental disorders in social networks.

PubMed

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro

2018-03-22

Heterogeneity of human beings leads to think and react differently to social phenomena. Awareness and homophily drive people to weigh interactions in social multiplex networks, influencing a potential contagion effect. To quantify the impact of heterogeneity on spreading dynamics, we propose a model of coevolution of social contagion and awareness, through the introduction of statistical estimators, in a weighted multiplex network. Multiplexity of networked individuals may trigger propagation enough to produce effects among vulnerable subjects experiencing distress, mental disorder, which represent some of the strongest predictors of suicidal behaviours. The exposure to suicide is emotionally harmful, since talking about it may give support or inadvertently promote it. To disclose the complex effect of the overlapping awareness on suicidal ideation spreading among disordered people, we also introduce a data-driven approach by integrating different types of data. Our modelling approach unveils the relationship between distress and mental disorders propagation and suicidal ideation spreading, shedding light on the role of awareness in a social network for suicide prevention. The proposed model is able to quantify the impact of overlapping awareness on suicidal ideation spreading and our findings demonstrate that it plays a dual role on contagion, either reinforcing or delaying the contagion outbreak.

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.

Early Predictors of Impaired Social Functioning in Male Rhesus Macaques (Macaca mulatta)

PubMed Central

Del Rosso, Laura A.; Seil, Shannon K.; Calonder, Laura A.; Madrid, Jesus E.; Bone, Kyle J.; Sherr, Elliott H.; Garner, Joseph P.; Capitanio, John P.; Parker, Karen J.

2016-01-01

Autism spectrum disorder (ASD) is characterized by social cognition impairments but its basic disease mechanisms remain poorly understood. Progress has been impeded by the absence of animal models that manifest behavioral phenotypes relevant to ASD. Rhesus monkeys are an ideal model organism to address this barrier to progress. Like humans, rhesus monkeys are highly social, possess complex social cognition abilities, and exhibit pronounced individual differences in social functioning. Moreover, we have previously shown that Low-Social (LS) vs. High-Social (HS) adult male monkeys exhibit lower social motivation and poorer social skills. It is not known, however, when these social deficits first emerge. The goals of this study were to test whether juvenile LS and HS monkeys differed as infants in their ability to process social information, and whether infant social abilities predicted later social classification (i.e., LS vs. HS), in order to facilitate earlier identification of monkeys at risk for poor social outcomes. Social classification was determined for N = 25 LS and N = 25 HS male monkeys that were 1–4 years of age. As part of a colony-wide assessment, these monkeys had previously undergone, as infants, tests of face recognition memory and the ability to respond appropriately to conspecific social signals. Monkeys later identified as LS vs. HS showed impairments in recognizing familiar vs. novel faces and in the species-typical adaptive ability to gaze avert to scenes of conspecific aggression. Additionally, multivariate logistic regression using infant social ability measures perfectly predicted later social classification of all N = 50 monkeys. These findings suggest that an early capacity to process important social information may account for differences in rhesus monkeys’ motivation and competence to establish and maintain social relationships later in life. Further development of this model will facilitate identification of novel biological targets for intervention to improve social outcomes in at-risk young monkeys. PMID:27788195

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.

Psycho-Cognitive Intervention for ASD from Cross-Species Behavioral Analyses of Infants, Chicks and Common Marmosets.

PubMed

Koshiba, Mamiko; Karino, Genta; Mimura, Koki; Nakamura, Shun; Yui, Kunio; Kunikata, Tetsuya; Yamanouchi, Hideo

2016-01-01

Educational treatment to support social development of children with autism spectrum disorder (ASD) is an important topic in developmental psychiatry. However, it remains difficult to objectively quantify the socio-emotional development of ASD children. To address this problem, we developed a novel analytical method that assesses subjects' complex behaviors using multivariate analysis, 'Behavior Output analysis for Quantitative Emotional State Translation' (BOUQUET). Here, we examine the potential for psycho-cognitive ASD therapy based on comparative evaluations of clinical (human) and experimental (animal) models. Our observations of ASD children (vs. their normally developing siblings) and the domestic chick in socio-sensory deprivation models show the importance of unimodal sensory stimulation, particularly important for tactile- and auditory-biased socialization. Identifying psycho-cognitive elements in early neural development, human newborn infants in neonatal intensive care unit as well as a New World monkey, the common marmoset, also prompted us to focus on the development of voluntary movement against gravity. In summary, striking behavioral similarities between children with ASD and domestic chicks' socio-sensory deprivation models support the role of multimodal sensory-motor integration as a prerequisite step for normal development of socio-emotional and psycho-cognitive functions. Data obtained in the common marmoset model also suggest that switching from primitive anti-gravity reflexes to complex voluntary movement may be a critical milestone for psycho-cognitive development. Combining clinical findings with these animal models, and using multivariate integrative analyses may facilitate the development of effective interventions to improve social functions in infants and in children with neurodevelopmental disorders.

Building flexibility and managing complexity in community mental health: lessons learned in a large urban centre.

PubMed

Stergiopoulos, Vicky; Saab, Dima; Francombe Pridham, Kate; Aery, Anjana; Nakhost, Arash

2018-01-24

Across many jurisdictions, adults with complex mental health and social needs face challenges accessing appropriate supports due to system fragmentation and strict eligibility criteria of existing services. To support this underserviced population, Toronto's local health authority launched two novel community mental health models in 2014, inspired by Flexible Assertive Community Team principles. This study explores service user and provider perspectives on the acceptability of these services, and lessons learned during early implementation. We purposively sampled 49 stakeholders (staff, physicians, service users, health systems stakeholders) and conducted 17 semi-structured qualitative interviews and 5 focus groups between October 23, 2014 and March 2, 2015, exploring stakeholder perspectives on the newly launched team based models, as well as activities and strategies employed to support early implementation. Interviews and focus groups were audio recorded, transcribed verbatim and analyzed using thematic analysis. Findings revealed wide-ranging endorsement for the two team-based models' success in engaging the target population of adults with complex service needs. Implementation strengths included the broad recognition of existing service gaps, the use of interdisciplinary teams and experienced service providers, broad partnerships and collaboration among various service sectors, training and team building activities. Emerging challenges included lack of complementary support services such as suitable housing, organizational contexts reluctant to embrace change and risk associated with complexity, as well as limited service provider and organizational capacity to deliver evidence-based interventions. Findings identified implementation drivers at the practitioner, program, and system levels, specific to the implementation of community mental health interventions for adults with complex health and social needs. These can inform future efforts to address the health and support needs of this vulnerable population.

Predicting future conflict between team-members with parameter-free models of social networks

NASA Astrophysics Data System (ADS)

Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

2013-06-01

Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

Cross Domain Deterrence: Livermore Technical Report, 2014-2016

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

Barnes, Peter D.; Bahney, Ben; Matarazzo, Celeste

2016-08-03

Lawrence Livermore National Laboratory (LLNL) is an original collaborator on the project titled “Deterring Complex Threats: The Effects of Asymmetry, Interdependence, and Multi-polarity on International Strategy,” (CDD Project) led by the UC Institute on Global Conflict and Cooperation at UCSD under PIs Jon Lindsay and Erik Gartzke , and funded through the DoD Minerva Research Initiative. In addition to participating in workshops and facilitating interaction among UC social scientists, LLNL is leading the computational modeling effort and assisting with empirical case studies to probe the viability of analytic, modeling and data analysis concepts. This report summarizes LLNL work on themore » CDD Project to date, primarily in Project Years 1-2, corresponding to Federal fiscal year 2015. LLNL brings two unique domains of expertise to bear on this Project: (1) access to scientific expertise on the technical dimensions of emerging threat technology, and (2) high performance computing (HPC) expertise, required for analyzing the complexity of bargaining interactions in the envisioned threat models. In addition, we have a small group of researchers trained as social scientists who are intimately familiar with the International Relations research. We find that pairing simulation scientists, who are typically trained in computer science, with domain experts, social scientists in this case, is the most effective route to developing powerful new simulation tools capable of representing domain concepts accurately and answering challenging questions in the field.« less

Interactive Cumulative Burden Assessment: Engaging Stakeholders in an Adaptive, Participatory and Transdisciplinary Approach

PubMed Central

Shrestha, Rehana; van Maarseveen, Martin

2018-01-01

Cumulative burden assessment (CuBA) has the potential to inform planning and decision-making on health disparities related to multiple environmental burdens. However, scholars have raised concerns about the social complexity to be dealt with while conducting CuBA, suggesting that it should be addressed in an adaptive, participatory and transdisciplinary (APT) approach. APT calls for deliberation among stakeholders by engaging them in a process of social learning and knowledge co-production. We propose an interactive stakeholder-based approach that facilitates a science-based stakeholder dialogue as an interface for combining different knowledge domains and engendering social learning in CuBA processes. Our approach allows participants to interact with each other using a flexible and auditable CuBA model implemented within a shared workspace. In two workshops we explored the usefulness and practicality of the approach. Results show that stakeholders were enabled to deliberate on cumulative burdens collaboratively, to learn about the technical uncertainties and social challenges associated with CuBA, and to co-produce knowledge in a realm of both technical and societal challenges. The paper identifies potential benefits relevant for responding to social complexity in the CuBA and further recommends exploration of how our approach can enable or constraint social learning and knowledge co-production in CuBA processes under various institutional, social and political contexts. PMID:29401676

Anthropology and cultural neuroscience: creating productive intersections in parallel fields.

PubMed

Brown, R A; Seligman, R

2009-01-01

Partly due to the failure of anthropology to productively engage the fields of psychology and neuroscience, investigations in cultural neuroscience have occurred largely without the active involvement of anthropologists or anthropological theory. Dramatic advances in the tools and findings of social neuroscience have emerged in parallel with significant advances in anthropology that connect social and political-economic processes with fine-grained descriptions of individual experience and behavior. We describe four domains of inquiry that follow from these recent developments, and provide suggestions for intersections between anthropological tools - such as social theory, ethnography, and quantitative modeling of cultural models - and cultural neuroscience. These domains are: the sociocultural construction of emotion, status and dominance, the embodiment of social information, and the dual social and biological nature of ritual. Anthropology can help locate unique or interesting populations and phenomena for cultural neuroscience research. Anthropological tools can also help "drill down" to investigate key socialization processes accountable for cross-group differences. Furthermore, anthropological research points at meaningful underlying complexity in assumed relationships between social forces and biological outcomes. Finally, ethnographic knowledge of cultural content can aid with the development of ecologically relevant stimuli for use in experimental protocols.

Behavioral and neural properties of social reinforcement learning

PubMed Central

Jones, Rebecca M.; Somerville, Leah H.; Li, Jian; Ruberry, Erika J.; Libby, Victoria; Glover, Gary; Voss, Henning U.; Ballon, Douglas J.; Casey, BJ

2011-01-01

Social learning is critical for engaging in complex interactions with other individuals. Learning from positive social exchanges, such as acceptance from peers, may be similar to basic reinforcement learning. We formally test this hypothesis by developing a novel paradigm that is based upon work in non-human primates and human imaging studies of reinforcement learning. The probability of receiving positive social reinforcement from three distinct peers was parametrically manipulated while brain activity was recorded in healthy adults using event-related functional magnetic resonance imaging (fMRI). Over the course of the experiment, participants responded more quickly to faces of peers who provided more frequent positive social reinforcement, and rated them as more likeable. Modeling trial-by-trial learning showed ventral striatum and orbital frontal cortex activity correlated positively with forming expectations about receiving social reinforcement. Rostral anterior cingulate cortex activity tracked positively with modulations of expected value of the cues (peers). Together, the findings across three levels of analysis - social preferences, response latencies and modeling neural responses – are consistent with reinforcement learning theory and non-human primate electrophysiological studies of reward. This work highlights the fundamental influence of acceptance by one’s peers in altering subsequent behavior. PMID:21917787

Analytical Sociology: A Bungean Appreciation

ERIC Educational Resources Information Center

Wan, Poe Yu-ze

2012-01-01

Analytical sociology, an intellectual project that has garnered considerable attention across a variety of disciplines in recent years, aims to explain complex social processes by dissecting them, accentuating their most important constituent parts, and constructing appropriate models to understand the emergence of what is observed. To achieve…

The challenge of causal inference in gene-environment interaction research: leveraging research designs from the social sciences.

PubMed

Fletcher, Jason M; Conley, Dalton

2013-10-01

The integration of genetics and the social sciences will lead to a more complex understanding of the articulation between social and biological processes, although the empirical difficulties inherent in this integration are large. One key challenge is the implications of moving "outside the lab" and away from the experimental tools available for research with model organisms. Social science research methods used to examine human behavior in nonexperimental, real-world settings to date have not been fully taken advantage of during this disciplinary integration, especially in the form of gene-environment interaction research. This article outlines and provides examples of several prominent research designs that should be used in gene-environment research and highlights a key benefit to geneticists of working with social scientists.

Coupled disease-behavior dynamics on complex networks: A review.

PubMed

Wang, Zhen; Andrews, Michael A; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years. Copyright © 2015 Elsevier B.V. All rights reserved.

Hypergraph topological quantities for tagged social networks.

PubMed

Zlatić, Vinko; Ghoshal, Gourab; Caldarelli, Guido

2009-09-01

Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.

Hypergraph topological quantities for tagged social networks

NASA Astrophysics Data System (ADS)

Zlatić, Vinko; Ghoshal, Gourab; Caldarelli, Guido

2009-09-01

Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.

Applying Weick's model of organizing to health care and health promotion: highlighting the central role of health communication.

PubMed

Kreps, Gary L

2009-03-01

Communication is a crucial process in the effective delivery of health care services and the promotion of public health. However, there are often tremendous complexities in using communication effectively to provide the best health care, direct the adoption of health promoting behaviors, and implement evidence-based public health policies and practices. This article describes Weick's model of organizing as a powerful theory of social organizing that can help increase understanding of the communication demands of health care and health promotion. The article identifies relevant applications from the model for health communication research and practice. Weick's model of organizing is a relevant and heuristic theoretical perspective for guiding health communication research and practice. There are many potential applications of this model illustrating the complexities of effective communication in health care and health promotion. Weick's model of organizing can be used as a template for guiding both research and practice in health care and health promotion. The model illustrates the important roles that communication performs in enabling health care consumers and providers to make sense of the complexities of modern health care and health promotion, select the best strategies for responding effectively to complex health care and health promotion situations, and retain relevant information (develop organizational intelligence) for guiding future responses to complex health care and health promotion challenges.

Social support, sense of community in school, and self-efficacy as resources during early adolescence: an integrative model.

PubMed

Vieno, Alessio; Santinello, Massimo; Pastore, Massimiliano; Perkins, Douglas D

2007-03-01

Influences of different sources of social support (from parents and friends), school sense of community, and self-efficacy on psychosocial well being (as measured by self-reported life satisfaction and psychological symptoms) in early adolescence were investigated in an integrative model. The model was tested using structural equation modeling. Multi-group comparisons were used to estimate differences between sex and age groups. The survey sample was composed of 7,097 students in Northern Italy (51.4% male) divided into three age cohorts (equivalent to 6th, 8th, and 10th grades with median ages of 11, 13, and 15). Findings obtained using SEM were consistent with self-efficacy and school sense of community mediating effects of social support on psychosocial adjustment. The multi-group comparison indicates a need for more complex developmental models and more research on how changing forms of support interact with each other as their effects also change during this important stage of the life. Implications for primary prevention and cross-cultural comparisons are discussed.

Model Minority Stereotyping, Perceived Discrimination, and Adjustment Among Adolescents from Asian American Backgrounds.

PubMed

Kiang, Lisa; Witkow, Melissa R; Thompson, Taylor L

2016-07-01

The model minority image is a common and pervasive stereotype that Asian American adolescents must navigate. Using multiwave data from 159 adolescents from Asian American backgrounds (mean age at initial recruitment = 15.03, SD = .92; 60 % female; 74 % US-born), the current study targeted unexplored aspects of the model minority experience in conjunction with more traditionally measured experiences of negative discrimination. When examining normative changes, perceptions of model minority stereotyping increased over the high school years while perceptions of discrimination decreased. Both experiences were not associated with each other, suggesting independent forms of social interactions. Model minority stereotyping generally promoted academic and socioemotional adjustment, whereas discrimination hindered outcomes. Moreover, in terms of academic adjustment, the model minority stereotype appears to protect against the detrimental effect of discrimination. Implications of the complex duality of adolescents' social interactions are discussed.

Does Social Context Matter? Income Inequality, Racialized Identity, and Health Among Canada's Aboriginal Peoples Using a Multilevel Approach.

PubMed

Spence, Nicholas D

2016-03-01

Debates surrounding the importance of social context versus individual level processes have a long history in public health. Aboriginal peoples in Canada are very diverse, and the reserve communities in which they reside are complex mixes of various cultural and socioeconomic circumstances. The social forces of these communities are believed to affect health, in addition to individual level determinants, but no large scale work has ever probed their relative effects. One aspect of social context, relative deprivation, as indicated by income inequality, has greatly influenced the social determinants of health landscape. An investigation of relative deprivation in Canada's Aboriginal population has never been conducted. This paper proposes a new model of Aboriginal health, using a multidisciplinary theoretical approach that is multilevel. This study explored the self-rated health of respondents using two levels of determinants, contextual and individual. Data were from the 2001 Aboriginal Peoples Survey. There were 18,890 Registered First Nations (subgroup of Aboriginal peoples) on reserve nested within 134 communities. The model was assessed using a hierarchical generalized linear model. There was no significant variation at the contextual level. Subsequently, a sequential logistic regression analysis was run. With the sole exception culture, demographics, lifestyle factors, formal health services, and social support were significant in explaining self-rated health. The non-significant effect of social context, and by extension relative deprivation, as indicated by income inequality, is noteworthy, and the primary role of individual level processes, including the material conditions, social support, and lifestyle behaviors, on health outcomes is illustrated. It is proposed that social structure is best conceptualized as a dynamic determinant of health inequality and more multilevel theoretical models of Aboriginal health should be developed and tested.

Complex contagions with timers

NASA Astrophysics Data System (ADS)

Oh, Se-Wook; Porter, Mason A.

2018-03-01

There has been a great deal of effort to try to model social influence—including the spread of behavior, norms, and ideas—on networks. Most models of social influence tend to assume that individuals react to changes in the states of their neighbors without any time delay, but this is often not true in social contexts, where (for various reasons) different agents can have different response times. To examine such situations, we introduce the idea of a timer into threshold models of social influence. The presence of timers on nodes delays adoptions—i.e., changes of state—by the agents, which in turn delays the adoptions of their neighbors. With a homogeneously-distributed timer, in which all nodes have the same amount of delay, the adoption order of nodes remains the same. However, heterogeneously-distributed timers can change the adoption order of nodes and hence the "adoption paths" through which state changes spread in a network. Using a threshold model of social contagions, we illustrate that heterogeneous timers can either accelerate or decelerate the spread of adoptions compared to an analogous situation with homogeneous timers, and we investigate the relationship of such acceleration or deceleration with respect to the timer distribution and network structure. We derive an analytical approximation for the temporal evolution of the fraction of adopters by modifying a pair approximation for the Watts threshold model, and we find good agreement with numerical simulations. We also examine our new timer model on networks constructed from empirical data.

Social Work Grand Challenges: Leaders' Perceptions of the Potential for Partnering with Business.

PubMed

Long, Ashley

2018-04-23

Social work's ability to address complex societal problems such as those identified in the American Academy of Social Work and Social Welfare's Grand Challenges for Social Work is reliant on being innovative in how we prepare social workers and how we collaborate with others, including business. This research seeks to understand how leaders of major social work organizations perceive potential partnership with the business sector-including both possible threats and opportunities. Interviews were conducted with those serving on the Council on Social Work Education's Leadership Roundtable. The research explores how emerging partnership models can be helpful and ways in which the profession can prepare practitioners for better partnering with the business sector. Qualitative findings identify four key strategies to address the grand challenges and enhance partnerships: (1) more interdisciplinary work is needed, (2) social work students need to be adequately equipped for collaborative work, (3) a cohesive message is needed from the field, and (4) the potential benefits for partnering with business outweigh the risks.

Using light gradients to investigate symmetry breaking in fish schools

NASA Astrophysics Data System (ADS)

Puckett, James; Giannini, Julia

Theoretical models of social animals successfully reproduce many structures found in nature (e.g. swarms, flocks, mills) using simple interaction rules. However, the interactions between individuals is complex and undoubtedly depends on the environment. Using schools of fish, we use visual perturbations to investigate how individuals negotiate both social and environmental information to reach a consensus. Starting with an unpolarized school of fish, we examine how the symmetry is broken and find that not all fish contribute equally to this decision.

Integrating Social Work into Palliative Care for Lung Cancer Patients and Families: A Multi-Dimensional Approach

PubMed Central

Otis-Green, Shirley; Sidhu, Rupinder K.; Ferraro, Catherine Del; Ferrell, Betty

2014-01-01

Lung cancer patients and their family caregivers face a wide range of potentially distressing symptoms across the four domains of quality of life. A multi-dimensional approach to addressing these complex concerns with early integration of palliative care has proven beneficial. This article highlights opportunities to integrate social work using a comprehensive quality of life model and a composite patient scenario from a large lung cancer educational intervention National Cancer Institute-funded program project grant. PMID:24797998

Understanding negative impacts of perceived cognitive load on job learning effectiveness: a social capital solution.

PubMed

Lin, Chieh-Peng

2010-12-01

This study proposes a model explaining how social capital helps ease excessively required mental effort. Although organizational researchers have studied both social capital and cognitive load, no prior research has critically examined the role of social capital in improving individuals' mental load and effort and consequently enhancing job learning effectiveness. This study surveys participants made up of professionals in Taiwan's information technology industry. It measures the constructs with the use of 5-point Likert-type scale items modified from existing literature. The survey data were analyzed with the use of structural equation modeling. Job learning effectiveness is negatively influenced by role ambiguity and role conflict. Time pressure has a positive influence on role ambiguity and role conflict Although the relationship between task complexity and role ambiguity is insignificant, task complexity has a positive influence on role conflict. Because the relationship between network ties and role conflict is insignificant, trust has a negative influence on role conflict. Last, shared vision has a negative influence on role ambiguity. This study provides an example of how social capital can be applied as a useful remedy to ease the negative impact of perceived cognitive load on job learning effectiveness. The negative relationship between shared vision and role ambiguity suggests that a shared vision helps in disseminating organizationally common goals and directions among employees to alleviate individuals' mental efforts in dealing with the ambiguity of their job roles. A firm's management team should take actions to decrease role conflict by strengthening trust among employees.

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.

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.

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

PubMed

de Greeff, Joachim; Belpaeme, Tony

2015-01-01

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.

Predictive model of complexity in early palliative care: a cohort of advanced cancer patients (PALCOM study).

PubMed

Tuca, Albert; Gómez-Martínez, Mónica; Prat, Aleix

2018-01-01

Model of early palliative care (PC) integrated in oncology is based on shared care from the diagnosis to the end of life and is mainly focused on patients with greater complexity. However, there is no definition or tools to evaluate PC complexity. The objectives of the study were to identify the factors influencing level determination of complexity, propose predictive models, and build a complexity scale of PC. We performed a prospective, observational, multicenter study in a cohort of advanced cancer patients with an estimated prognosis ≤ 6 months. An ad hoc structured evaluation including socio-demographic and clinical data, symptom burden, functional and cognitive status, psychosocial problems, and existential-ethic dilemmas was recorded systematically. According to this multidimensional evaluation, investigator classified patients as high, medium, or low palliative complexity, associated to need of basic or specialized PC. Logistic regression was used to identify the variables influencing determination of level of PC complexity and explore predictive models. We included 324 patients; 41% were classified as having high PC complexity and 42.9% as medium, both levels being associated with specialized PC. Variables influencing determination of PC complexity were as follows: high symptom burden (OR 3.19 95%CI: 1.72-6.17), difficult pain (OR 2.81 95%CI:1.64-4.9), functional status (OR 0.99 95%CI:0.98-0.9), and social-ethical existential risk factors (OR 3.11 95%CI:1.73-5.77). Logistic analysis of variables allowed construct a complexity model and structured scales (PALCOM 1 and 2) with high predictive value (AUC ROC 76%). This study provides a new model and tools to assess complexity in palliative care, which may be very useful to manage referral to specialized PC services, and agree intensity of their intervention in a model of early-shared care integrated in oncology.

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.

Mind the fish: zebrafish as a model in cognitive social neuroscience

PubMed Central

Oliveira, Rui F.

2013-01-01

Understanding how the brain implements social behavior on one hand, and how social processes feedback on the brain to promote fine-tuning of behavioral output according to changes in the social environment is a major challenge in contemporary neuroscience. A critical step to take this challenge successfully is finding the appropriate level of analysis when relating social to biological phenomena. Given the enormous complexity of both the neural networks of the brain and social systems, the use of a cognitive level of analysis (in an information processing perspective) is proposed here as an explanatory interface between brain and behavior. A conceptual framework for a cognitive approach to comparative social neuroscience is proposed, consisting of the following steps to be taken across different species with varying social systems: (1) identification of the functional building blocks of social skills; (2) identification of the cognitive mechanisms underlying the previously identified social skills; and (3) mapping these information processing mechanisms onto the brain. Teleost fish are presented here as a group of choice to develop this approach, given the diversity of social systems present in closely related species that allows for planned phylogenetic comparisons, and the availability of neurogenetic tools that allows the visualization and manipulation of selected neural circuits in model species such as the zebrafish. Finally, the state-of-the art of zebrafish social cognition and of the tools available to map social cognitive abilities to neural circuits in zebrafish are reviewed. PMID:23964204

Mind the fish: zebrafish as a model in cognitive social neuroscience.

PubMed

Oliveira, Rui F

2013-01-01

Understanding how the brain implements social behavior on one hand, and how social processes feedback on the brain to promote fine-tuning of behavioral output according to changes in the social environment is a major challenge in contemporary neuroscience. A critical step to take this challenge successfully is finding the appropriate level of analysis when relating social to biological phenomena. Given the enormous complexity of both the neural networks of the brain and social systems, the use of a cognitive level of analysis (in an information processing perspective) is proposed here as an explanatory interface between brain and behavior. A conceptual framework for a cognitive approach to comparative social neuroscience is proposed, consisting of the following steps to be taken across different species with varying social systems: (1) identification of the functional building blocks of social skills; (2) identification of the cognitive mechanisms underlying the previously identified social skills; and (3) mapping these information processing mechanisms onto the brain. Teleost fish are presented here as a group of choice to develop this approach, given the diversity of social systems present in closely related species that allows for planned phylogenetic comparisons, and the availability of neurogenetic tools that allows the visualization and manipulation of selected neural circuits in model species such as the zebrafish. Finally, the state-of-the art of zebrafish social cognition and of the tools available to map social cognitive abilities to neural circuits in zebrafish are reviewed.

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

What Difference Does It Make? Implicit, Explicit and Complex Social Cognition in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Schaller, Ulrich M.; Rauh, Reinhold

2017-01-01

We tested social cognition abilities of adolescents with autism spectrum disorders (ASD) and neurotypically developed peers (NTD). A multi-faceted test-battery including facial emotion categorization (FEC), classical false belief tasks (FBT), and complex social cognition (SC), yielded significantly lower accuracy rates for FEC and complex SC tasks…

Some Better Practices for Measuring Racial and Ethnic Identity Constructs

ERIC Educational Resources Information Center

Helms, Janet E.

2007-01-01

Racial and ethnic identity (REI) measures are in danger of becoming conceptually meaningless because of evaluators' insistence that they conform to measurement models intended to assess unidimensional constructs, rather than the multidimensional constructs necessary to capture the complexity of internalized racial or cultural socialization. Some…

Pigs as laboratory animals

USDA-ARS?s Scientific Manuscript database

The pig is increasingly popular as a laboratory animal either as the target species in its own right or as a model for humans in biomedical science. As an intelligent, social animal it has a complex behavioral repertoire reminiscent of its ancestor, the wild boar. Within a laboratory setting, the pi...

Using an Ethical Decision-Making Model to Address Ethical Dilemmas in School Counseling

ERIC Educational Resources Information Center

Brown, Timothy; Armstrong, Stephen A.; Bore, Samuel; Simpson, Chris

2017-01-01

School counselors frequently face ethical dilemmas. These dilemmas often involve relationships with principals, parents, and other stakeholders. School counselors may confront complex ethical issues involving confidentiality, student safety, parental rights,and social media. The American School Counselor Association recommends following an ethical…

Current use was established and Cochrane guidance on selection of social theories for systematic reviews of complex interventions was developed.

PubMed

Noyes, Jane; Hendry, Maggie; Booth, Andrew; Chandler, Jackie; Lewin, Simon; Glenton, Claire; Garside, Ruth

2016-07-01

To identify examples of how social theories are used in systematic reviews of complex interventions to inform production of Cochrane guidance. Secondary analysis of published/unpublished examples of theories of social phenomena for use in reviews of complex interventions identified through scoping searches, engagement with key authors and methodologists supplemented by snowballing and reference searching. Theories were classified (low-level, mid-range, grand). Over 100 theories were identified with evidence of proliferation over the last 5 years. New low-level theories (tools, taxonomies, etc) have been developed for classifying and reporting complex interventions. Numerous mid-range theories are used; one example demonstrated how control theory had changed the review's findings. Review-specific logic models are increasingly used, but these can be challenging to develop. New low-level and mid-range psychological theories of behavior change are evolving. No reviews using grand theory (e.g., feminist theory) were identified. We produced a searchable Wiki, Mendeley Inventory, and Cochrane guidance. Use of low-level theory is common and evolving; incorporation of mid-range theory is still the exception rather than the norm. Methodological work is needed to evaluate the contribution of theory. Choice of theory reflects personal preference; application of theory is a skilled endeavor. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Complex land use and cover trajectories in the northern Choco bioregion of Colombia

NASA Astrophysics Data System (ADS)

Santos, Carolina

The Choco bioregion in Northwestern Colombia is a lowland rain forest and hotspot of biodiversity. Significant land use and cover change (LUCC) is occurring throughout the region driven by global markets, illicit drug production, and civil unrest. The dominant land cover conversion is from primary forest to African Palm plantations, mediated and modified by complex combinations of social and biophysical drivers. This research combined a remote sensing based methodology to monitor LUCC in the region with an analytical approach for evaluating the possible trajectories of LUCC in a complex biological, socio-economical, and political environment. Synoptic LUCC models were developed using textural classification derived from Synthetic Aperture Radar (SAR) images for the period 1995 to 2010. LUCC models along with empirical social and spatial biophysical drivers were used to project historical land use trajectories. DINAMICA EGO a complex systems based spatial analytical framework was adopted as the platform to model land use change. The RADAR backscatter was able to capture areas were forest has been converted to African Oil Palm Plantations. However, an in depth characterization of the LUC dynamics was problematic given the spectral and spatial limitations of the sensor combined with the lack of ground data. The results of the LUC model suggest that under the current socio-political conditions African oil palm plantations will continue to expand toward forested areas into the territories traditionally inhabited by Afro-Colombians and Indigenous populations. Insecure land tenure appears as a main driver of the transformation in close association with the conditions created by the armed conflict, and the drug traffic. The rate of the transformation appears to slow down in the period after 2007. However, according to the model by 2020 most of the area inhabited by ethnic groups will be transform to AOP. This study contributes towards the understanding of land use change in the context of social conflict. Although, it is recognized that conflicts impact the land--use and land-cover, few studies have address the linkages between particular circumstances and events in the conflict and the consequences for the land. As resource conflicts spread around the globe a better understanding of how it impacts the land and the people is paramount.

Complex investigation of the effects of lambertianic acid amide in female mice under conditions of social discomfort.

PubMed

Avgustinovich, D F; Fomina, M K; Sorokina, I V; Tolstikova, T G

2014-09-01

The effects of chronic administration of a new substance lambertianic acid amide and previously synthesized methyl ester of this acid were compared in female mice living under conditions of social discomfort. For modeling social discomfort, female mouse was housed for 30 days in a cage with aggressive male mouse kept behind a transparent perforated partition and observed its confrontations with another male mouse daily placed to the cage. The new agent more effectively than lambertianic acid methyl ester improved communicativeness and motor activity of animals, reduced hypertrophy of the adrenal glands, and enhanced catalase activity in the blood. These changes suggest that lambertianic acid amide produces a pronounced stress-protective effect under conditions of social discomfort.

A new similarity measure for link prediction based on local structures in social networks

NASA Astrophysics Data System (ADS)

Aghabozorgi, Farshad; Khayyambashi, Mohammad Reza

2018-07-01

Link prediction is a fundamental problem in social network analysis. There exist a variety of techniques for link prediction which applies the similarity measures to estimate proximity of vertices in the network. Complex networks like social networks contain structural units named network motifs. In this study, a newly developed similarity measure is proposed where these structural units are applied as the source of similarity estimation. This similarity measure is tested through a supervised learning experiment framework, where other similarity measures are compared with this similarity measure. The classification model trained with this similarity measure outperforms others of its kind.

Testing equivalence of mediating models of income, parenting, and school readiness for white, black, and Hispanic children in a national sample.

PubMed

Raver, C Cybele; Gershoff, Elizabeth T; Aber, J Lawrence

2007-01-01

This paper examines complex models of the associations between family income, material hardship, parenting, and school readiness among White, Black, and Hispanic 6-year-olds, using the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K). It is critical to test the universality of such complex models, particularly given their implications for intervention, prevention, and public policy. Therefore this study asks: Do measures and models of low income and early school readiness indicators fit differently or similarly for White, Black, and Hispanic children? Measurement equivalence of material hardship, parent stress, parenting behaviors, child cognitive skills, and child social competence is first tested. Model equivalence is then tested by examining whether category membership in a race/ethnic group moderates associations between predictors and young children's school readiness.

Testing Equivalence of Mediating Models of Income, Parenting, and School Readiness for White, Black, and Hispanic Children in a National Sample

PubMed Central

Raver, C. Cybele; Gershoff, Elizabeth T.; Aber, J. Lawrence

2010-01-01

This paper examines complex models of the associations between family income, material hardship, parenting, and school readiness among White, Black, and Hispanic 6-year-olds, using the Early Childhood Longitudinal Study – Kindergarten Cohort (ECLS – K). It is critical to test the universality of such complex models, particularly given their implications for intervention, prevention, and public policy. Therefore this study asks: Do measures and models of low income and early school readiness indicators fit differently or similarly for White, Black, and Hispanic children? Measurement equivalence of material hardship, parent stress, parenting behaviors, child cognitive skills, and child social competence is first tested. Model equivalence is then tested by examining whether category membership in a race/ethnic group moderates associations between predictors and young children’s school readiness. PMID:17328695

[Social actors and phenomenologic modelling].

PubMed

Laflamme, Simon

2012-05-01

The phenomenological approach has a quasi-monopoly in the individual and subjectivity analyses in social sciences. However, the conceptual apparatus associated with this approach is very restrictive. The human being has to be understood as rational, conscious, intentional, interested, and autonomous. Because of this, a large dimension of human activity cannot be taken into consideration: all that does not fit into the analytical categories (nonrational, nonconscious, etc.). Moreover, this approach cannot really move toward a relational analysis unless it is between individuals predefined by its conceptual apparatus. This lack of complexity makes difficult the establishment of links between phenomenology and systemic analysis in which relation (and its derivatives such as recursiveness, dialectic, correlation) plays an essential role. This article intends to propose a way for systemic analysis to apprehend the individual with respect to his complexity.

Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception.

PubMed

Mottron, Laurent; Dawson, Michelle; Soulières, Isabelle; Hubert, Benedicte; Burack, Jake

2006-01-01

We propose an "Enhanced Perceptual Functioning" model encompassing the main differences between autistic and non-autistic social and non-social perceptual processing: locally oriented visual and auditory perception, enhanced low-level discrimination, use of a more posterior network in "complex" visual tasks, enhanced perception of first order static stimuli, diminished perception of complex movement, autonomy of low-level information processing toward higher-order operations, and differential relation between perception and general intelligence. Increased perceptual expertise may be implicated in the choice of special ability in savant autistics, and in the variability of apparent presentations within PDD (autism with and without typical speech, Asperger syndrome) in non-savant autistics. The overfunctioning of brain regions typically involved in primary perceptual functions may explain the autistic perceptual endophenotype.

A generalized theory of preferential linking

NASA Astrophysics Data System (ADS)

Hu, Haibo; Guo, Jinli; Liu, Xuan; Wang, Xiaofan

2014-12-01

There are diverse mechanisms driving the evolution of social networks. A key open question dealing with understanding their evolution is: How do various preferential linking mechanisms produce networks with different features? In this paper we first empirically study preferential linking phenomena in an evolving online social network, find and validate the linear preference. We propose an analyzable model which captures the real growth process of the network and reveals the underlying mechanism dominating its evolution. Furthermore based on preferential linking we propose a generalized model reproducing the evolution of online social networks, and present unified analytical results describing network characteristics for 27 preference scenarios. We study the mathematical structure of degree distributions and find that within the framework of preferential linking analytical degree distributions can only be the combinations of finite kinds of functions which are related to rational, logarithmic and inverse tangent functions, and extremely complex network structure will emerge even for very simple sublinear preferential linking. This work not only provides a verifiable origin for the emergence of various network characteristics in social networks, but bridges the micro individuals' behaviors and the global organization of social networks.

Creating a professional development platform to transform social work clinical practice in health care.

PubMed

Xenakis, Nancy

2018-07-01

Since U.S. Congress' 2010 passing of the Affordable Care Act and the creation of numerous care coordination programs, Mount Sinai Hospital's Department of Social Work Services has experienced exponential growth. The Department is deeply committed to recruiting and developing the most talented social workers to best meet the needs of patients and family caregivers and to serve as integral, valued members of interdisciplinary care teams. Traditional learning methods are insufficient for a staff of hundreds, given the changes in health care and the complexity of the work. This necessitates the use of new training and education methods to maintain the quality of professional development. This article provides an overview of the Department's strategy and creation of a professional development learning platform to transform clinical social work practice. It reviews various education models that utilize an e-learning management system and case studies using standardized patients. These models demonstrate innovative learning approaches for both new and experienced social workers in health care. The platform's successes and challenges and recommendations for future development and sustainability are outlined.

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.

Social disinhibition is a heritable subphenotype of tics in Tourette syndrome

PubMed Central

Hirschtritt, Matthew E.; Darrow, Sabrina M.; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert A.; Pauls, David L.; Budman, Cathy L.; Cath, Danielle C.; Greenberg, Erica; Lyon, Gholson J.; Yu, Dongmei; McGrath, Lauren M.; McMahon, William M.; Lee, Paul C.; Delucchi, Kevin L.; Scharf, Jeremiah M.

2016-01-01

Objective: To identify heritable symptom-based subtypes of Tourette syndrome (TS). Methods: Forty-nine motor and phonic tics were examined in 3,494 individuals (1,191 TS probands and 2,303 first-degree relatives). Item-level exploratory factor and latent class analyses (LCA) were used to identify tic-based subtypes. Heritabilities of the subtypes were estimated, and associations with clinical characteristics were examined. Results: A 6-factor exploratory factor analysis model provided the best fit, which paralleled the somatotopic representation of the basal ganglia, distinguished simple from complex tics, and separated out socially disinhibited and compulsive tics. The 5-class LCA model best distinguished among the following groups: unaffected, simple tics, intermediate tics without social disinhibition, intermediate with social disinhibition, and high rates of all tic types. Across models, a phenotype characterized by high rates of social disinhibition emerged. This phenotype was associated with increased odds of comorbid psychiatric disorders, in particular, obsessive-compulsive disorder and attention-deficit/hyperactivity disorder, earlier age at TS onset, and increased tic severity. The heritability estimate for this phenotype based on the LCA was 0.53 (SE 0.08, p 1.7 × 10−18). Conclusions: Expanding on previous modeling approaches, a series of TS-related phenotypes, including one characterized by high rates of social disinhibition, were identified. These phenotypes were highly heritable and may reflect underlying biological networks more accurately than traditional diagnoses, thus potentially aiding future genetic, imaging, and treatment studies. PMID:27371487

Social disinhibition is a heritable subphenotype of tics in Tourette syndrome.

PubMed

Hirschtritt, Matthew E; Darrow, Sabrina M; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert A; Pauls, David L; Budman, Cathy L; Cath, Danielle C; Greenberg, Erica; Lyon, Gholson J; Yu, Dongmei; McGrath, Lauren M; McMahon, William M; Lee, Paul C; Delucchi, Kevin L; Scharf, Jeremiah M; Mathews, Carol A

2016-08-02

To identify heritable symptom-based subtypes of Tourette syndrome (TS). Forty-nine motor and phonic tics were examined in 3,494 individuals (1,191 TS probands and 2,303 first-degree relatives). Item-level exploratory factor and latent class analyses (LCA) were used to identify tic-based subtypes. Heritabilities of the subtypes were estimated, and associations with clinical characteristics were examined. A 6-factor exploratory factor analysis model provided the best fit, which paralleled the somatotopic representation of the basal ganglia, distinguished simple from complex tics, and separated out socially disinhibited and compulsive tics. The 5-class LCA model best distinguished among the following groups: unaffected, simple tics, intermediate tics without social disinhibition, intermediate with social disinhibition, and high rates of all tic types. Across models, a phenotype characterized by high rates of social disinhibition emerged. This phenotype was associated with increased odds of comorbid psychiatric disorders, in particular, obsessive-compulsive disorder and attention-deficit/hyperactivity disorder, earlier age at TS onset, and increased tic severity. The heritability estimate for this phenotype based on the LCA was 0.53 (SE 0.08, p 1.7 × 10(-18)). Expanding on previous modeling approaches, a series of TS-related phenotypes, including one characterized by high rates of social disinhibition, were identified. These phenotypes were highly heritable and may reflect underlying biological networks more accurately than traditional diagnoses, thus potentially aiding future genetic, imaging, and treatment studies. © 2016 American Academy of Neurology.

Physics of human cooperation: experimental evidence and theoretical models

NASA Astrophysics Data System (ADS)

Sánchez, Angel

2018-02-01

In recent years, many physicists have used evolutionary game theory combined with a complex systems perspective in an attempt to understand social phenomena and challenges. Prominent among such phenomena is the issue of the emergence and sustainability of cooperation in a networked world of selfish or self-focused individuals. The vast majority of research done by physicists on these questions is theoretical, and is almost always posed in terms of agent-based models. Unfortunately, more often than not such models ignore a number of facts that are well established experimentally, and are thus rendered irrelevant to actual social applications. I here summarize some of the facts that any realistic model should incorporate and take into account, discuss important aspects underlying the relation between theory and experiments, and discuss future directions for research based on the available experimental knowledge.

How multiple social networks affect user awareness: The information diffusion process in multiplex networks

NASA Astrophysics Data System (ADS)

Li, Weihua; Tang, Shaoting; Fang, Wenyi; Guo, Quantong; Zhang, Xiao; Zheng, Zhiming

2015-10-01

The information diffusion process in single complex networks has been extensively studied, especially for modeling the spreading activities in online social networks. However, individuals usually use multiple social networks at the same time, and can share the information they have learned from one social network to another. This phenomenon gives rise to a new diffusion process on multiplex networks with more than one network layer. In this paper we account for this multiplex network spreading by proposing a model of information diffusion in two-layer multiplex networks. We develop a theoretical framework using bond percolation and cascading failure to describe the intralayer and interlayer diffusion. This allows us to obtain analytical solutions for the fraction of informed individuals as a function of transmissibility T and the interlayer transmission rate θ . Simulation results show that interaction between layers can greatly enhance the information diffusion process. And explosive diffusion can occur even if the transmissibility of the focal layer is under the critical threshold, due to interlayer transmission.

Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

NASA Astrophysics Data System (ADS)

Wu, Yu'E.; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

2017-01-01

Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.

Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

PubMed Central

Wu, Yu’e; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

2017-01-01

Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world. PMID:28112276

Exploratory of society

NASA Astrophysics Data System (ADS)

Cederman, L.-E.; Conte, R.; Helbing, D.; Nowak, A.; Schweitzer, F.; Vespignani, A.

2012-11-01

A huge flow of quantitative social, demographic and behavioral data is becoming available that traces the activities and interactions of individuals, social patterns, transportation infrastructures and travel fluxes. This has caused, together with innovative computational techniques and methods for modeling social actions in hybrid (natural and artificial) societies, a qualitative change in the ways we model socio-technical systems. For the first time, society can be studied in a comprehensive fashion that addresses social and behavioral complexity. In other words we are in the position to envision the development of large data and computational cyber infrastructure defining an exploratory of society that provides quantitative anticipatory, explanatory and scenario analysis capabilities ranging from emerging infectious disease to conflict and crime surges. The goal of the exploratory of society is to provide the basic infrastructure embedding the framework of tools and knowledge needed for the design of forecast/anticipatory/crisis management approaches to socio technical systems, supporting future decision making procedures by accelerating the scientific cycle that goes from data generation to predictions.

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.

Constructing and Modifying Sequence Statistics for relevent Using informR in 𝖱

PubMed Central

Marcum, Christopher Steven; Butts, Carter T.

2015-01-01

The informR package greatly simplifies the analysis of complex event histories in 𝖱 by providing user friendly tools to build sufficient statistics for the relevent package. Historically, building sufficient statistics to model event sequences (of the form a→b) using the egocentric generalization of Butts’ (2008) relational event framework for modeling social action has been cumbersome. The informR package simplifies the construction of the complex list of arrays needed by the rem() model fitting for a variety of cases involving egocentric event data, multiple event types, and/or support constraints. This paper introduces these tools using examples from real data extracted from the American Time Use Survey. PMID:26185488

In vivo neurometabolic profiling to characterize the effects of social isolation and ketamine-induced NMDA antagonism: a rodent study at 7.0 T.

PubMed

Napolitano, Antonio; Shah, Khalid; Schubert, Mirjam I; Porkess, Veronica; Fone, Kevin C F; Auer, Dorothee P

2014-05-01

Continued efforts are undertaken to develop animal models of schizophrenia with translational value in the quest for much needed novel drugs. Existing models mimic specific neurobiological aspects of schizophrenia, but not its full complexity. Here, we used proton magnetic resonance spectroscopy ((1)H-MRS) to assess the metabolic profile in the prefrontal cortex (PFC) of two established models, rearing in social isolation and acute N-methyl-D-aspartate receptor (NMDA-R) antagonism and their combination. Rats reared in social isolation or group housed underwent (1)H-MRS at baseline and dynamically after ketamine challenge (25mg/kg, intraperitoneal) under isoflurane anesthesia. A 7 T animal scanner was used to perform spectra acquisition from the anterior cingulate/medial PFC. LCModel was used for metabolite quantification and effects of rearing and ketamine injection were analyzed. Social isolation did not lead to significant differences in the metabolic profile of the PFC at baseline. Ketamine induced a significant increase in glutamine in both groups with significance specifically reached by the group-housed animals alone. Only rats reared in social isolation showed a significant 11% γ-aminobutyric acid (GABA) decrease. This study provides preliminary evidence that social interactions in early life predict the glutamatergic and GABAergic response to acute NMDA-R blockade. The similarity between the prefrontal GABA reduction in patients with schizophrenia and in rats reared as social isolates after challenge with ketamine suggests good potential translational value of this combined animal model for drug development.

In Vivo Neurometabolic Profiling to Characterize the Effects of Social Isolation and Ketamine-Induced NMDA Antagonism: A Rodent Study at 7.0 T

PubMed Central

Napolitano, Antonio

2014-01-01

Continued efforts are undertaken to develop animal models of schizophrenia with translational value in the quest for much needed novel drugs. Existing models mimic specific neurobiological aspects of schizophrenia, but not its full complexity. Here, we used proton magnetic resonance spectroscopy (1H-MRS) to assess the metabolic profile in the prefrontal cortex (PFC) of two established models, rearing in social isolation and acute N-methyl-d-aspartate receptor (NMDA-R) antagonism and their combination. Rats reared in social isolation or group housed underwent ​1H-MRS at baseline and dynamically after ketamine challenge (25mg/kg, intraperitoneal) under isoflurane anesthe sia. A 7 T animal scanner was used to perform spectra acquisition from the anterior cingulate/medial PFC. LCModel was used for metabolite quantification and effects of rearing and ketamine injection were analyzed. Social isolation did not lead to significant differences in the metabolic profile of the PFC at baseline. Ketamine induced a significant increase in glutamine in both groups with significance specifically reached by the group-housed animals alone. Only rats reared in social isolation showed a significant 11% γ-aminobutyric acid (GABA) decrease. This study provides preliminary evidence that social interactions in early life predict the glutamatergic and GABAergic response to acute NMDA-R blockade. The similarity between the prefrontal GABA reduction in patients with schizophrenia and in rats reared as social isolates after challenge with ketamine suggests good potential translational value of this combined animal model for drug development. PMID:23671195

The Challenge of Translation in Social Neuroscience: A Review of Oxytocin, Vasopressin, and Affiliative Behavior

PubMed Central

Insel, Thomas R.

2010-01-01

Social neuroscience is rapidly exploring the complex territory between perception and action where recognition, value, and meaning are instantiated. This review follows the trail of research on oxytocin and vasopressin as an exemplar of one path for exploring the “dark matter” of social neuroscience. Studies across vertebrate species suggest that these neuropeptides are important for social cognition, with gender and steroid-dependent effects. Comparative research in voles yields a model based on inter-species and intra-species variation of the geography of oxytocin receptors and vasopressin V1a receptors in the forebrain. Highly affiliative species have receptors in brain circuits related to reward or reinforcement. The neuroanatomical distribution of these receptors may be guided by variations in the regulatory regions of their respective genes. This review describes the promises and problems of extrapolating these findings to human social cognition, with specific reference to the social deficits of autism. PMID:20346754

Teacher Efficacy, Work Engagement, and Social Support Among Chinese Special Education School Teachers

PubMed Central

Minghui, Lu; Lei, Hao; Xiaomeng, Chen; Potměšilc, Miloň

2018-01-01

This paper investigates the relationship between teacher efficacy and socio-demographic factors, work engagement, and social support among Chinese special education school teachers. The sample comprised 1,027 special education school teachers in mainland China. The Teachers’ Sense of Efficacy Scale, the Multi-Dimensional Scale of Perceived Social Support, and the Utrecht Work Engagement Scale were used for data collection. Correlation analysis revealed that social support, work engagement, and teacher efficacy were significantly correlated with each other. Additionally, gender, years of experience, and monthly salary were significant predictors of teacher efficacy. Furthermore, structural equation modeling analysis showed that social support exerted its indirect effect on teacher efficacy through the mediation of work engagement. The findings of this study provide a new perspective on the complex association between social support and teacher efficacy. The explanations and limitations of these findings are discussed. PMID:29867634

Social cognitive conflict resolution: Contributions of domain general and domain specific neural systems

PubMed Central

Zaki, Jamil; Hennigan, Kelly; Weber, Jochen; Ochsner, Kevin N.

2010-01-01

Cognitive control mechanisms allow individuals to behave adaptively in the face of complex and sometimes conflicting information. While the neural bases of these control mechanisms have been examined in many contexts, almost no attention has been paid to their role in resolving conflicts between competing social cues, which is surprising, given that cognitive conflicts are part of many social interactions. Evidence about the neural processing of social information suggests that two systems—the mirror neuron system (MNS) and mental state attribution system (MSAS)—are specialized for processing nonverbal and contextual social cues, respectively. This could support a model of social cognitive conflict resolution in which competition between social cues would recruit domain-general cognitive control mechanisms, which in turn would bias processing towards the MNS or MSAS. Such biasing could also alter social behaviors, such as inferences made about the internal states of others. We tested this model by scanning participants using fMRI while they drew inferences about social targets' emotional states based on congruent or incongruent nonverbal and contextual social cues. Conflicts between social cues recruited the anterior cingulate and lateral prefrontal cortex, brain areas associated with domain-general control processes. This activation was accompanied by biasing of neural activity towards areas in the MNS or MSAS, which tracked, respectively, with perceivers' behavioral reliance on nonverbal or contextual cues when drawing inferences about targets' emotions. Together, these data provide evidence about both domain general and domain specific mechanisms involved in resolving social cognitive conflicts. PMID:20573895

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

PubMed Central

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency. PMID:26609303

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

PubMed

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

[Associations and dissociations: agents, discourses and controversies surrounding child hyperactivity].

PubMed

García, Inmaculada Hurtado

2017-01-01

Attention deficit hyperactivity disorder (ADHD) generates debates and confrontations among diverse social agents with different conceptions of normality, health, the individual and the social. In this scenario of controversy, parents have tried to improve the living conditions of their children through a number of models of social participation in health. Using a qualitative ethnographic approach, fieldwork was carried out from 2013 to 2015 with the purpose of analyzing the universe of organizations regarding ADHD in Spain as well as other individual parenting initiatives with collective repercussions. The work seeks to identify the different relationships with expert knowledge in existence and the models of knowledge circulation that take place within those relationships, focusing on the way they configure discursive stances, establish collective dynamics, and develop actions. The disputed character of ADHD is evidenced in models more complex than that of the expert/layperson duality, as well as in new strategies of production and collectivization of knowledge facilitated by the Internet.

The influence of tie strength on evolutionary games on networks: An empirical investigation

NASA Astrophysics Data System (ADS)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

Choosing embryos: ethical complexity and relational autonomy in staff accounts of PGD

PubMed Central

Ehrich, Kathryn; Williams, Clare; Farsides, Bobbie; Sandall, Jane; Scott, Rosamund

2007-01-01

The technique of preimplantation genetic diagnosis (PGD) is commonly explained as a way of checking the genes of embryos produced by IVF for serious genetic diseases. However, complex accounts of this technique emerged during ethics discussion groups held for PGD staff. These form part of a study exploring the social processes, meanings and institutions that frame and produce ‘ethical problems’ for practitioners, scientists and others working in the specialty of PGD in the UK. Two ‘grey areas’ raised by staff are discussed in terms of how far staff are, or in the future may be, able to support autonomous choices of women/couples: accepting ‘carrier’ embryos within the goal of creating a ‘healthy’ child; and sex selection of embryos for social reasons. These grey areas challenged the staff's resolve to offer individual informed choice, in the face of their awareness of possible collective social effects that might ensue from individual choices. We therefore argue that these new forms of choice pose a challenge to conventional models of individual autonomy used in UK genetic and reproductive counselling, and that ‘relational autonomy’ may be a more suitable ethical model to describe the ethical principles being drawn on by staff working in this area. PMID:18092985

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.

What adult worker model? A critical look at recent social policy reform in Europe from a gender and family perspective.

PubMed

Daly, Mary

2011-01-01

Analyses regularly feature claims that European welfare states are in the process of creating an adult worker model. The theoretical and empirical basis of this argument is examined here by looking first at the conceptual foundations of the adult worker model formulation and then at the extent to which social policy reform in western Europe fits with the argument. It is suggested that the adult worker formulation is under-specified. A framework incorporating four dimensions—the treatment of individuals vis-à-vis their family role and status for the purposes of social rights, the treatment of care, the treatment of the family as a social institution, and the extent to which gender inequality is problematized—is developed and then applied. The empirical analysis reveals a strong move towards individualization as social policy promotes and valorizes individual agency and self-sufficiency and shifts some childcare from the family. Yet evidence is also found of continued (albeit changed) familism. Rather than an unequivocal move to an individualized worker model then, a dual earner, gender-specialized, family arrangement is being promoted. The latter is the middle way between the old dependencies and the new “independence.” This makes for complexity and even ambiguity in policy, a manifestation of which is that reform within countries involves concurrent moves in several directions.

mTOR inhibitor reverses autistic-like social deficit behaviours in adult rats with both Tsc2 haploinsufficiency and developmental status epilepticus.

PubMed

Schneider, Miriam; de Vries, Petrus J; Schönig, Kai; Rößner, Veit; Waltereit, Robert

2017-08-01

Epilepsy is a major risk factor for autism spectrum disorder (ASD) and complicates clinical manifestations and management of ASD significantly. Tuberous sclerosis complex (TSC), caused by TSC1 or TSC2 mutations, is one of the medical conditions most commonly associated with ASD and has become an important model to examine molecular pathways associated with ASD. Previous research showed reversal of autism-like social deficits in Tsc1 +/- and Tsc2 +/- mouse models by mammalian target of rapamycin (mTOR) inhibitors. However, at least 70 % of individuals with TSC also have epilepsy, known to complicate the severity and treatment responsiveness of the behavioural phenotype. No previous study has examined the impact of seizures on neurocognitive reversal by mTOR inhibitors. Adult Tsc2 +/- (Eker)-rats express social deficits similar to Tsc2 +/- mice, with additive social deficits from developmental status epilepticus (DSE). DSE was induced by intraperitoneal injection with kainic acid at post-natal days P7 and P14 (n = 12). The experimental group that modelled TSC pathology carried the Tsc2 +/- (Eker)-mutation and was challenged with DSE. The wild-type controls had not received DSE (n = 10). Four-month-old animals were analysed for social behaviour (T1), then treated three times during 1 week with 1 mg/kg everolimus and finally retested in the post-treatment behavioural analysis (T2). In the experimental group, both social interaction and social cognition were impaired at T1. After treatment at T2, behaviour in the experimental group was indistinguishable from controls. The mTOR inhibitor, everolimus, reversed social deficit behaviours in the Tsc2 haploinsufficiency plus DSE animal model to control levels.

An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

NASA Astrophysics Data System (ADS)

Hu, Xiaolin; Puddy, Richard W.

This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

Infection dynamics on spatial small-world network models

NASA Astrophysics Data System (ADS)

Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario

2017-11-01

The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.

Parent-Child Play across Cultures: Advancing Play Research

ERIC Educational Resources Information Center

Roopnarine, Jaipaul L.; Davidson, Kimberly L.

2015-01-01

In this article, the authors argue for a greater understanding of children's play across cultures through better integration of scientific thinking about the developed and developing societies, through consideration of socialization beliefs and goals, and, finally, through the use of more complex models in research investigations. They draw on…

Bulimia: A Model for Group Therapy.

ERIC Educational Resources Information Center

Bauer, Barbara G.

Bulimia, an eating disorder characterized by binge eating followed by purging and intense feelings of guilt and failure, is increasing among young women. The eating behavior is only a symptom of more complex underlying problems such as feelings of inadequacy, social isolation, depression, rigid thinking, self-defeating thoughts, and perfectionism.…

A Longitudinal Integration of Identity Styles and Educational Identity Processes in Adolescence

ERIC Educational Resources Information Center

Negru-Subtirica, Oana; Pop, Eleonora Ioana; Crocetti, Elisabetta

2017-01-01

Identity formation is a main adolescent psychosocial developmental task. The complex interconnection between different processes that are at the basis of one's identity is a research and applied intervention priority. In this context, the identity style model focuses on social-cognitive strategies (i.e., informational, normative, and…

Group Therapy for Survivors of Severe Childhood Abuse: Repairing the Social Contract.

ERIC Educational Resources Information Center

Scott, Wayne

1999-01-01

Presents a model for conducting time-limited group therapy with adult survivors of severe childhood abuse who were diagnosed with complex post-traumatic and dissociative disorders. Group sessions are organized around verbal promises that encourage the client's active, attentive engagement. Gentle confrontation of dissociative defenses is integral…

An individual-based modeling approach to simulating recreation use in wilderness settings

Treesearch

Randy Gimblett; Terry Daniel; Michael J. Meitner

2000-01-01

Landscapes protect biological diversity and provide unique opportunities for human-nature interactions. Too often, these desirable settings suffer from extremely high visitation. Given the complexity of social, environmental and economic interactions, resource managers need tools that provide insights into the cause and effect relationships between management actions...

Inferring High-Resolution Individual’s Activity and Trip Purposes with the Fusion of Social Media, Land Use and Connected Vehicle Trajectories

DOT National Transportation Integrated Search

2017-11-30

Trip purpose is crucial to travel behavior modeling and travel demand estimation for transportation planning and investment decisions. However, the spatial-temporal complexity of human activities makes the prediction of trip purpose a challenging pro...

Characteristics Associated with Sleep Duration, Chronotype, and Social Jet Lag in Adolescents

ERIC Educational Resources Information Center

Malone, Susan Kohl; Zemel, Babette; Compher, Charlene; Souders, Margaret; Chittams, Jesse; Thompson, Aleda Leis; Lipman, Terri H.

2016-01-01

Sleep is a complex behavior with numerous health implications. Identifying sociodemographic and behavioral characteristics of sleep is important for determining those at greatest risk for sleep-related health disparities. In this cross-sectional study, general linear models were used to examine sociodemographic and behavioral characteristics…

The Journey toward Developing Political Consciousness through Activism for Mexican American Women

ERIC Educational Resources Information Center

Hernandez, Ebelia

2012-01-01

This study examined how Mexican American women made meaning of their undergraduate activism and its potential implications on their development toward self-authorship. The developing political consciousness model emerged from their interviews to demonstrate the process of developing increasingly complex social knowledge, the shift of motivation to…

STRATOP: A Model for Designing Effective Product and Communication Strategies. Paper No. 470.

ERIC Educational Resources Information Center

Pessemier, Edgar A.

The STRATOP algorithm was developed to help planners and proponents find and test effectively designed choice objects and communication strategies. Choice objects can range from complex social, scientific, military, or educational alternatives to simple economic alternatives between assortments of branded convenience goods. Two classes of measured…

Undergraduate Students' Development of Social, Cultural, and Human Capital in a Networked Research Experience

ERIC Educational Resources Information Center

Thompson, Jennifer Jo; Conaway, Evan; Dolan, Erin L.

2016-01-01

Recent calls for reform in undergraduate biology education have emphasized integrating research experiences into the learning experiences of all undergraduates. Contemporary science research increasingly demands collaboration across disciplines and institutions to investigate complex research questions, providing new contexts and models for…

School System Simulation: An Effective Model for Educational Leaders.

ERIC Educational Resources Information Center

Nelson, Jorge O.

This study reviews the literature regarding the theoretical rationale for creating a computer-based school system simulation for educational leaders' use in problem solving and decision making. Like all social systems, educational systems are so complex that individuals are hard-pressed to consider all interrelated parts as a totality. A…

Psychosocial and cognitive factors associated with adherence to dietary and fluid restriction regimens by people on chronic haemodialysis.

PubMed

Sensky, T; Leger, C; Gilmour, S

1996-01-01

Failure by people on chronic haemodialysis to adhere adequately to dietary and fluid restrictions can have serious medical consequences. Numerous psychosocial factors possibly associated with adherence have been investigated in previous research. However, most previous studies have examined one or a few variables in isolation, and have tended to focus on sociodemographic variables not easily amenable to intervention. Much previous work has tended to ignore potential differences in adherence between male and female dialysands. Sociodemographic and psychosocial factors associated with adherence to dietary and fluid restrictions were investigated in 45 people on haemodialysis attending one renal unit, excluding those with a residual urine volume > 500 ml/day. Multiple regression analyses were used to estimate the contribution to adherence of a range of variables, including gender, age, duration of dialysis, affective disturbance, past psychiatric history, health locus of control, social adjustment and social supports. Adherence to diet (measured by predialysis serum potassium) and to fluid restriction (interdialysis weight gain) were not linked, and had different psychosocial correlates. Regression models of four different aspects of adherence revealed very distinct psychosocial correlates, with contributions to adherence from complex interactions between psychosocial and cognitive variables, notably gender, age, social adjustment, health locus of control, and depression. The findings cast doubt on the results of many previous studies which have used simple models of adherence. Adherence is likely to be influenced in a complex manner by multiple factors including age, gender, locus of control, social adjustment, and past psychiatric history.

The evolutionary basis of human social learning

PubMed Central

Morgan, T. J. H.; Rendell, L. E.; Ehn, M.; Hoppitt, W.; Laland, K. N.

2012-01-01

Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules. PMID:21795267

The evolutionary basis of human social learning.

PubMed

Morgan, T J H; Rendell, L E; Ehn, M; Hoppitt, W; Laland, K N

2012-02-22

Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.

Bilinear effect in complex systems

NASA Astrophysics Data System (ADS)

Lam, Lui; Bellavia, David C.; Han, Xiao-Pu; Alston Liu, Chih-Hui; Shu, Chang-Qing; Wei, Zhengjin; Zhou, Tao; Zhu, Jichen

2010-09-01

The distribution of the lifetime of Chinese dynasties (as well as that of the British Isles and Japan) in a linear Zipf plot is found to consist of two straight lines intersecting at a transition point. This two-section piecewise-linear distribution is different from the power law or the stretched exponent distribution, and is called the Bilinear Effect for short. With assumptions mimicking the organization of ancient Chinese regimes, a 3-layer network model is constructed. Numerical results of this model show the bilinear effect, providing a plausible explanation of the historical data. The bilinear effect in two other social systems is presented, indicating that such a piecewise-linear effect is widespread in social systems.

Social network models predict movement and connectivity in ecological landscapes

USGS Publications Warehouse

Fletcher, R.J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, W.M.

2011-01-01

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Selection to outsmart the germs: The evolution of disease recognition and social cognition.

PubMed

Kessler, Sharon E; Bonnell, Tyler R; Byrne, Richard W; Chapman, Colin A

2017-07-01

The emergence of providing care to diseased conspecifics must have been a turning point during the evolution of hominin sociality. On a population level, care may have minimized the costs of socially transmitted diseases at a time of increasing social complexity, although individual care-givers probably incurred increased transmission risks. We propose that care-giving likely originated within kin networks, where the costs may have been balanced by fitness increases obtained through caring for ill kin. We test a novel hypothesis of hominin cognitive evolution in which disease may have selected for the cognitive ability to recognize when a conspecific is infected. Because diseases may produce symptoms that are likely detectable via the perceptual-cognitive pathways integral to social cognition, we suggest that disease recognition and social cognition may have evolved together. Using agent-based modeling, we test 1) under what conditions disease can select for increasing disease recognition and care-giving among kin, 2) whether providing care produces greater selection for cognition than an avoidance strategy, and 3) whether care-giving alters the progression of the disease through the population. The greatest selection was produced by diseases with lower risks to the care-giver and prevalences low enough not to disrupt the kin networks. When care-giving and avoidance strategies were compared, only care-giving reduced the severity of the disease outbreaks and subsequent population crashes. The greatest selection for increased cognitive abilities occurred early in the model runs when the outbreaks and population crashes were most severe. Therefore, over the course of human evolution, repeated introductions of novel diseases into naïve populations could have produced sustained selection for increased disease recognition and care-giving behavior, leading to the evolution of increased cognition, social complexity, and, eventually, medical care in humans. Finally, we lay out predictions derived from our disease recognition hypothesis that we encourage paleoanthropologists, bioarchaeologists, primatologists, and paleogeneticists to test. Copyright © 2017 Elsevier Ltd. All rights reserved.

Knowledge Co-production Strategies for Water Resources Modeling and Decision Making

NASA Astrophysics Data System (ADS)

Gober, P.

2016-12-01

The limited impact of scientific information on policy making and climate adaptation in North America has raised awareness of the need for new modeling strategies and knowledge transfer processes. This paper outlines the rationale for a new paradigm in water resources modeling and management, using examples from the USA and Canada. Principles include anticipatory modeling, complex system dynamics, decision making under uncertainty, visualization, capacity to represent and manipulate critical trade-offs, stakeholder engagement, local knowledge, context-specific activities, social learning, vulnerability analysis, iterative and collaborative modeling, and the concept of a boundary organization. In this framework, scientists and stakeholders are partners in the production and dissemination of knowledge for decision making, and local knowledge is fused with scientific observation and methodology. Discussion draws from experience in building long-term collaborative boundary organizations in Phoenix, Arizona in the USA and the Saskatchewan River Basin (SRB) in Canada. Examples of boundary spanning activities include the use of visualization, the concept of a decision theater, infrastructure to support social learning, social networks, and reciprocity, simulation modeling to explore "what if" scenarios of the future, surveys to elicit how water problems are framed by scientists and stakeholders, and humanistic activities (theatrical performances, art exhibitions, etc.) to draw attention to local water issues. The social processes surrounding model development and dissemination are at least as important as modeling assumptions, procedures, and results in determining whether scientific knowledge will be used effectively for water resources decision making.

Constructing a self: the role of self-structure and self-certainty in social anxiety.

PubMed

Stopa, Lusia; Brown, Mike A; Luke, Michelle A; Hirsch, Colette R

2010-10-01

Current cognitive models stress the importance of negative self-perceptions in maintaining social anxiety, but focus predominantly on content rather than structure. Two studies examine the role of self-structure (self-organisation, self-complexity, and self-concept clarity) in social anxiety. In study one, self-organisation and self-concept clarity were correlated with social anxiety, and a step-wise multiple regression showed that after controlling for depression and self-esteem, which explained 35% of the variance in social anxiety scores, self-concept clarity uniquely predicted social anxiety and accounted for an additional 7% of the variance in social anxiety scores in an undergraduate sample (N=95) and the interaction between self-concept clarity and compartmentalisation (an aspect of evaluative self-organisation) at step 3 of the multiple regression accounted for a further 3% of the variance in social anxiety scores. In study two, high (n=26) socially anxious participants demonstrated less self-concept clarity than low socially anxious participants (n=26) on both self-report (used in study one) and on computerised measures of self-consistency and confidence in self-related judgments. The high socially anxious group had more compartmentalised self-organisation than the low anxious group, but there were no differences between the two groups on any of the other measures of self-organisation. Self-complexity did not contribute to social anxiety in either study, although this may have been due to the absence of a stressor. Overall, the results suggest that self-structure has a potentially important role in understanding social anxiety and that self-concept clarity and other aspects of self-structure such as compartmentalisation interact with each other and could be potential maintaining factors in social anxiety. Cognitive therapy for social phobia might influence self-structure, and understanding the role of structural variables in maintenance and treatment could eventually help to improve treatment outcome. Copyright 2010 Elsevier Ltd. All rights reserved.

Constructing a self: The role of self-structure and self-certainty in social anxiety

PubMed Central

Stopa, Lusia; Brown, Mike A.; Luke, Michelle A.; Hirsch, Colette R.

2010-01-01

Current cognitive models stress the importance of negative self-perceptions in maintaining social anxiety, but focus predominantly on content rather than structure. Two studies examine the role of self-structure (self-organisation, self-complexity, and self-concept clarity) in social anxiety. In study one, self-organisation and self-concept clarity were correlated with social anxiety, and a step-wise multiple regression showed that after controlling for depression and self-esteem, which explained 35% of the variance in social anxiety scores, self-concept clarity uniquely predicted social anxiety and accounted for an additional 7% of the variance in social anxiety scores in an undergraduate sample (N = 95) and the interaction between self-concept clarity and compartmentalisation (an aspect of evaluative self-organisation) at step 3 of the multiple regression accounted for a further 3% of the variance in social anxiety scores. In study two, high (n = 26) socially anxious participants demonstrated less self-concept clarity than low socially anxious participants (n = 26) on both self-report (used in study one) and on computerised measures of self-consistency and confidence in self-related judgments. The high socially anxious group had more compartmentalised self-organisation than the low anxious group, but there were no differences between the two groups on any of the other measures of self-organisation. Self-complexity did not contribute to social anxiety in either study, although this may have been due to the absence of a stressor. Overall, the results suggest that self-structure has a potentially important role in understanding social anxiety and that self-concept clarity and other aspects of self-structure such as compartmentalisation interact with each other and could be potential maintaining factors in social anxiety. Cognitive therapy for social phobia might influence self-structure, and understanding the role of structural variables in maintenance and treatment could eventually help to improve treatment outcome. PMID:20800751

Model-Based Approaches for Teaching and Practicing Personality Assessment.

PubMed

Blais, Mark A; Hopwood, Christopher J

2017-01-01

Psychological assessment is a complex professional skill. Competence in assessment requires an extensive knowledge of personality, neuropsychology, social behavior, and psychopathology, a background in psychometrics, familiarity with a range of multimethod tools, cognitive flexibility, skepticism, and interpersonal sensitivity. This complexity makes assessment a challenge to teach and learn, particularly as the investment of resources and time in assessment has waned in psychological training programs over the last few decades. In this article, we describe 3 conceptual models that can assist teaching and learning psychological assessments. The transtheoretical model of personality provides a personality systems-based framework for understanding how multimethod assessment data relate to major personality systems and can be combined to describe and explain complex human behavior. The quantitative psychopathology-personality trait model is an empirical model based on the hierarchical organization of individual differences. Application of this model can help students understand diagnostic comorbidity and symptom heterogeneity, focus on more meaningful high-order domains, and identify the most effective assessment tools for addressing a given question. The interpersonal situation model is rooted in interpersonal theory and can help students connect test data to here-and-now interactions with patients. We conclude by demonstrating the utility of these models using a case example.

A Carbon Cycle Model for the Social-Ecological Process in Coastal Wetland: A Case Study on Gouqi Island, East China

PubMed Central

Xiong, Lihu; Zhu, Wenjia

2017-01-01

Coastal wetlands offer many important ecosystem services both in natural and in social systems. How to simultaneously decrease the destructive effects flowing from human activities and maintaining the sustainability of regional wetland ecosystems are an important issue for coastal wetlands zones. We use carbon credits as the basis for regional sustainable developing policy-making. With the case of Gouqi Island, a typical coastal wetlands zone that locates in the East China Sea, a carbon cycle model was developed to illustrate the complex social-ecological processes. Carbon-related processes in natural ecosystem, primary industry, secondary industry, tertiary industry, and residents on the island were identified in the model. The model showed that 36780 tons of carbon is released to atmosphere with the form of CO2, and 51240 tons of carbon is captured by the ecosystem in 2014 and the three major resources of carbon emission are transportation and tourism development and seawater desalination. Based on the carbon-related processes and carbon balance, we proposed suggestions on the sustainable development strategy of Gouqi Island as coastal wetlands zone. PMID:28286690

A Carbon Cycle Model for the Social-Ecological Process in Coastal Wetland: A Case Study on Gouqi Island, East China.

PubMed

Li, Yanxia; Xiong, Lihu; Zhu, Wenjia

2017-01-01

Coastal wetlands offer many important ecosystem services both in natural and in social systems. How to simultaneously decrease the destructive effects flowing from human activities and maintaining the sustainability of regional wetland ecosystems are an important issue for coastal wetlands zones. We use carbon credits as the basis for regional sustainable developing policy-making. With the case of Gouqi Island, a typical coastal wetlands zone that locates in the East China Sea, a carbon cycle model was developed to illustrate the complex social-ecological processes. Carbon-related processes in natural ecosystem, primary industry, secondary industry, tertiary industry, and residents on the island were identified in the model. The model showed that 36780 tons of carbon is released to atmosphere with the form of CO 2 , and 51240 tons of carbon is captured by the ecosystem in 2014 and the three major resources of carbon emission are transportation and tourism development and seawater desalination. Based on the carbon-related processes and carbon balance, we proposed suggestions on the sustainable development strategy of Gouqi Island as coastal wetlands zone.

Hydrological Responses of Andean Lakes and Tropical Floodplains to Climate Variability and Human Intervention: an Integrative Modelling Framework

NASA Astrophysics Data System (ADS)

Hoyos, I. C.; González Morales, C.; Serna López, J. P.; Duque, C. L.; Canon Barriga, J. E.; Dominguez, F.

2013-12-01

Andean water bodies in tropical regions are significantly influenced by fluctuations associated with climatic and anthropogenic drivers, which implies long term changes in mountain snow peaks, land covers and ecosystems, among others. Our work aims at providing an integrative framework to realistically assess the possible future of natural water bodies with different degrees of human intervention. We are studying in particular the evolution of three water bodies in Colombia: two Andean lakes and a floodplain wetland. These natural reservoirs represent the accumulated effect of hydrological processes in their respective basins, which exhibit different patterns of climate variability and distinct human intervention and environmental histories. Modelling the hydrological responses of these local water bodies to climate variability and human intervention require an understanding of the strong linkage between geophysical and social factors. From the geophysical perspective, the challenge is how to downscale global climate projections in the local context: complex orography and relative lack of data. To overcome this challenge we combine the correlational and physically based analysis of several sources of spatially distributed biophysical and meteorological information to accurately determine aspects such as moisture sources and sinks and past, present and future local precipitation and temperature regimes. From the social perspective, the challenge is how to adequately represent and incorporate into the models the likely response of social agents whose water-related interests are diverse and usually conflictive. To deal with the complexity of these systems we develop interaction matrices, which are useful tools to holistically discuss and represent each environment as a complex system. Our goal is to assess partially the uncertainties of the hydrological balances in these intervened water bodies we establish climate/social scenarios, using hybrid models that combine the computational power of numerical simulations (of both physical and social components) with interactive responses given by users who define strategies and make decisions in real time, providing valuable information about people's attitudes and choices regarding future climate perspectives. Part of our interest with this project is to effectively transfer the knowledge and scientific information gathered to the communities in a way that is useful and propositive. To this end we developed a website (http://peerlagoscolombia.udea.edu.co) that includes relevant information about the project outcomes. We also developed and installed telemetric hydrologic stations in each site, whose data on water storage levels and basic meteorological variables can be accessed online. Acknowledgement: this project is funded by the USAID-NSF PEER program (First cycle, project 31).

Social activity, cognitive decline and dementia risk: a 20-year prospective cohort study.

PubMed

Marioni, Riccardo E; Proust-Lima, Cecile; Amieva, Helene; Brayne, Carol; Matthews, Fiona E; Dartigues, Jean-Francois; Jacqmin-Gadda, Helene

2015-10-24

Identifying modifiable lifestyle correlates of cognitive decline and risk of dementia is complex, particularly as few population-based longitudinal studies jointly model these interlinked processes. Recent methodological developments allow us to examine statistically defined sub-populations with separate cognitive trajectories and dementia risks. Engagement in social, physical, or intellectual pursuits, social network size, self-perception of feeling well understood, and degree of satisfaction with social relationships were assessed in 2854 participants from the Paquid cohort (mean baseline age 77 years) and related to incident dementia and cognitive change over 20-years of follow-up. Multivariate repeated cognitive information was exploited by defining the global cognitive functioning as the latent common factor underlying the tests. In addition, three latent homogeneous sub-populations of cognitive change and dementia were identified and contrasted according to social environment variables. In the whole population, we found associations between increased engagement in social, physical, or intellectual pursuits and increased cognitive ability (but not decline) and decreased risk of incident dementia, and between feeling understood and slower cognitive decline. There was evidence for three sub-populations of cognitive aging: fast, medium, and no cognitive decline. The social-environment measures at baseline did not help explain the heterogeneity of cognitive decline and incident dementia diagnosis between these sub-populations. We observed a complex series of relationships between social-environment variables and cognitive decline and dementia. In the whole population, factors such as increased engagement in social, physical, or intellectual pursuits were related to a decreased risk of dementia. However, in a sub-population analysis, the social-environment variables were not linked to the heterogeneous patterns of cognitive decline and dementia risk that defined the sub-groups.

Supporting Complex Problems: An Examination of Churchman’s Inquirers as a Knowledge Management Foundation

DTIC Science & Technology

2006-06-07

inquirers based on the underlying philosophies of Leibniz, Locke, Kant , Hegel, and Singer. These inquirers share capabilities and can work together in a...encourages and supports socially oriented knowledge development. The Kantian Inquirer Kantian systems are the archetype of multi-model, synthetic systems...Mason and Mitroff, 1973). The Kantian inquirer is designed to incorporate both multiple perspectives and facts to determine models that are