Co-rumination buffers the link between social anxiety and depressive symptoms in early adolescence.

PubMed

Van Zalk, Nejra; Tillfors, Maria

2017-01-01

We examined whether co-rumination with online friends buffered the link between social anxiety and depressive symptoms over time in a community sample. In a sample of 526 participants (358 girls; M age  = 14.05) followed at three time points, we conducted a latent cross-lagged model with social anxiety, depressive symptoms, and co-rumination, controlling for friendship stability and friendship quality, and adding a latent interaction between social anxiety and co-rumination predicting depressive symptoms. Social anxiety predicted depressive symptoms, but no direct links between social anxiety and co-rumination emerged. Instead, co-rumination buffered the link between social anxiety and depressive symptoms for adolescents with higher but not lower levels of social anxiety. These findings indicate that co-rumination exerted a positive influence on interpersonal relationships by diminishing the influence from social anxiety on depressive symptoms over time.

An efficient link prediction index for complex military organization

NASA Astrophysics Data System (ADS)

Fan, Changjun; Liu, Zhong; Lu, Xin; Xiu, Baoxin; Chen, Qing

2017-03-01

Quality of information is crucial for decision-makers to judge the battlefield situations and design the best operation plans, however, real intelligence data are often incomplete and noisy, where missing links prediction methods and spurious links identification algorithms can be applied, if modeling the complex military organization as the complex network where nodes represent functional units and edges denote communication links. Traditional link prediction methods usually work well on homogeneous networks, but few for the heterogeneous ones. And the military network is a typical heterogeneous network, where there are different types of nodes and edges. In this paper, we proposed a combined link prediction index considering both the nodes' types effects and nodes' structural similarities, and demonstrated that it is remarkably superior to all the 25 existing similarity-based methods both in predicting missing links and identifying spurious links in a real military network data; we also investigated the algorithms' robustness under noisy environment, and found the mistaken information is more misleading than incomplete information in military areas, which is different from that in recommendation systems, and our method maintained the best performance under the condition of small noise. Since the real military network intelligence must be carefully checked at first due to its significance, and link prediction methods are just adopted to purify the network with the left latent noise, the method proposed here is applicable in real situations. In the end, as the FINC-E model, here used to describe the complex military organizations, is also suitable to many other social organizations, such as criminal networks, business organizations, etc., thus our method has its prospects in these areas for many tasks, like detecting the underground relationships between terrorists, predicting the potential business markets for decision-makers, and so on.

Psychosocial mechanisms linking the social environment to mental health in African Americans

USDA-ARS?s Scientific Manuscript database

Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African Amer...

Social goals, aggression, peer preference, and popularity: longitudinal links during middle school.

PubMed

Ojanen, Tiina; Findley-Van Nostrand, Danielle

2014-08-01

Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic (status, power) goals predicted increased relational aggression and communal (closeness) goals predicted decreased physical aggression. Popularity predicted increases and preference predicted decreases in both forms of aggression. Goals moderated longitudinal links between aggression and popularity: Aggression predicted increases in popularity and vice versa for youth with higher agentic goals, and popularity predicted increases in physical aggression for youth with higher agentic and lower communal goals. Implications for research on social goals, aggression, and popularity are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Mixed-method Exploration of Social Network Links to Participation

PubMed Central

Kreider, Consuelo M.; Bendixen, Roxanna M.; Mann, William C.; Young, Mary Ellen; McCarty, Christopher

2015-01-01

The people who regularly interact with an adolescent form that youth's social network, which may impact participation. We investigated the relationship of social networks to participation using personal network analysis and individual interviews. The sample included 36 youth, age 11 – 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least one measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within social networks. Findings contribute to understanding the ways social networks are linked to youth participation and suggest the potential of social network factors for predicting rehabilitation outcomes. PMID:26594737

A link prediction approach to cancer drug sensitivity prediction.

PubMed

Turki, Turki; Wei, Zhi

2017-10-03

Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine. In this paper, we model cancer drug sensitivity as a link prediction, which is shown to be an effective technique. We evaluate our proposed link prediction algorithms and compare them with an existing drug sensitivity prediction approach based on clinical trial data. The experimental results based on the clinical trial data show the stability of our link prediction algorithms, which yield the highest area under the ROC curve (AUC) and are statistically significant. We propose a link prediction approach to obtain new feature representation. Compared with an existing approach, the results show that incorporating the new feature representation to the link prediction algorithms has significantly improved the performance.

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

Dysregulated fear predicts social wariness and social anxiety symptoms during kindergarten.

PubMed

Buss, Kristin A; Davis, Elizabeth L; Kiel, Elizabeth J; Brooker, Rebecca J; Beekman, Charles; Early, Martha C

2013-01-01

Fearful temperament is associated with risk for the development of social anxiety disorder in childhood; however, not all fearful children become anxious. Identifying maladaptive trajectories is thus important for clarifying which fearful children are at risk. In an unselected sample of 111 two-year-olds (55% male, 95% Caucasian), Buss ( 2011 ) identified a pattern of fearful behavior, dysregulated fear, characterized by high fear in low threat situations. This pattern of behavior predicted parent- and teacher-reported withdrawn/anxious behaviors in preschool and at kindergarten entry. The current study extended original findings and examined whether dysregulated fear predicted observed social wariness with adults and peers, and social anxiety symptoms at age 6. We also examined prosocial adjustment during kindergarten as a moderator of the link between dysregulated fear and social wariness. Consistent with predictions, children with greater dysregulated fear at age 2 were more socially wary of adults and unfamiliar peers in the laboratory, were reported as having more social anxiety symptoms, and were nearly 4 times more likely to manifest social anxiety symptoms than other children with elevated wariness in kindergarten. Results demonstrated stability in the dysregulated fear profile and increased risk for social anxiety symptom development. Dysregulated fear predicted more social wariness with unfamiliar peers only when children became less prosocial during kindergarten. Findings are discussed in relation to the utility of the dysregulated fear construct for specifying maladaptive trajectories of risk for anxiety disorder development.

Dysregulated Fear Predicts Social Wariness and Social Anxiety Symptoms during Kindergarten

PubMed Central

Buss, Kristin A.; Davis, Elizabeth L.; Kiel, Elizabeth J.; Brooker, Rebecca J.; Beekman, Charles; Early, Martha C.

2013-01-01

Fearful temperament is associated with risk for the development of social anxiety disorder in childhood; however, not all fearful children become anxious. Identifying maladaptive trajectories is thus important for clarifying which fearful children are at risk. In an unselected sample of 111 two-year-olds (55% male, 95% Caucasian), Buss (2011) identified a pattern of fearful behavior, dysregulated fear, characterized by high fear in low threat situations. This pattern of behavior predicted parent- and teacher-reported withdrawn/anxious behaviors in preschool and at kindergarten entry. The current study extended original findings and examined whether dysregulated fear predicted observed social wariness with adults and peers, and social anxiety symptoms at age 6. We also examined prosocial adjustment during kindergarten as a moderator of the link between dysregulated fear and social wariness. Consistent with predictions, children with greater dysregulated fear at age 2 were more socially wary of adults and unfamiliar peers in the laboratory, were reported as having more social anxiety symptoms, and were nearly four times more likely to manifest social anxiety symptoms than other children with elevated wariness in kindergarten. Results demonstrated stability in the dysregulated fear profile and increased risk for social anxiety symptom development. Dysregulated fear predicted more social wariness with unfamiliar peers only when children became less prosocial during kindergarten. Findings are discussed in relation to the utility of the dysregulated fear construct for specifying maladaptive trajectories of risk for anxiety disorder development. PMID:23458273

Toward link predictability of complex networks

PubMed Central

Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene

2015-01-01

The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742

Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

PubMed Central

Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

2016-01-01

The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

Utility-Based Link Recommendation in Social Networks

ERIC Educational Resources Information Center

Li, Zhepeng

2013-01-01

Link recommendation, which suggests links to connect currently unlinked users, is a key functionality offered by major online social networking platforms. Salient examples of link recommendation include "people you may know"' on Facebook and "who to follow" on Twitter. A social networking platform has two types of stakeholder:…

The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems

PubMed Central

Reafee, Waleed; Salim, Naomie; Khan, Atif

2016-01-01

The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy. PMID:27152663

Community detection in complex networks using link prediction

NASA Astrophysics Data System (ADS)

Cheng, Hui-Min; Ning, Yi-Zi; Yin, Zhao; Yan, Chao; Liu, Xin; Zhang, Zhong-Yuan

2018-01-01

Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from different perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improving the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baselines. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.

Link prediction based on local community properties

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Zhang, Hai-Feng; Ling, Fei; Cheng, Zhi; Weng, Guo-Qing; Huang, Yu-Jiao

2016-09-01

The link prediction algorithm is one of the key technologies to reveal the inherent rule of network evolution. This paper proposes a novel link prediction algorithm based on the properties of the local community, which is composed of the common neighbor nodes of any two nodes in the network and the links between these nodes. By referring to the node degree and the condition of assortativity or disassortativity in a network, we comprehensively consider the effect of the shortest path and edge clustering coefficient within the local community on node similarity. We numerically show the proposed method provide good link prediction results.

Predicting links based on knowledge dissemination in complex network

NASA Astrophysics Data System (ADS)

Zhou, Wen; Jia, Yifan

2017-04-01

Link prediction is the task of mining the missing links in networks or predicting the next vertex pair to be connected by a link. A lot of link prediction methods were inspired by evolutionary processes of networks. In this paper, a new mechanism for the formation of complex networks called knowledge dissemination (KD) is proposed with the assumption of knowledge disseminating through the paths of a network. Accordingly, a new link prediction method-knowledge dissemination based link prediction (KDLP)-is proposed to test KD. KDLP characterizes vertex similarity based on knowledge quantity (KQ) which measures the importance of a vertex through H-index. Extensive numerical simulations on six real-world networks demonstrate that KDLP is a strong link prediction method which performs at a higher prediction accuracy than four well-known similarity measures including common neighbors, local path index, average commute time and matrix forest index. Furthermore, based on the common conclusion that an excellent link prediction method reveals a good evolving mechanism, the experiment results suggest that KD is a considerable network evolving mechanism for the formation of complex networks.

Meta-path based heterogeneous combat network link prediction

NASA Astrophysics Data System (ADS)

Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

2017-09-01

The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

Exploring the social dimension of sandy beaches through predictive modelling.

PubMed

Domínguez-Tejo, Elianny; Metternicht, Graciela; Johnston, Emma L; Hedge, Luke

2018-05-15

Sandy beaches are unique ecosystems increasingly exposed to human-induced pressures. Consistent with emerging frameworks promoting this holistic approach towards beach management, is the need to improve the integration of social data into management practices. This paper aims to increase understanding of links between demographics and community values and preferred beach activities, as key components of the social dimension of the beach environment. A mixed method approach was adopted to elucidate users' opinions on beach preferences and community values through a survey carried out in Manly Local Government Area in Sydney Harbour, Australia. A proposed conceptual model was used to frame demographic models (using age, education, employment, household income and residence status) as predictors of these two community responses. All possible regression-model combinations were compared using Akaike's information criterion. Best models were then used to calculate quantitative likelihoods of the responses, presented as heat maps. Findings concur with international research indicating the relevance of social and restful activities as important social links between the community and the beach environment. Participant's age was a significant variable in the four predictive models. The use of predictive models informed by demographics could potentially increase our understanding of interactions between the social and ecological systems of the beach environment, as a prelude to integrated beach management approaches. The research represents a practical demonstration of how demographic predictive models could support proactive approaches to beach management. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predicting missing links via correlation between nodes

NASA Astrophysics Data System (ADS)

Liao, Hao; Zeng, An; Zhang, Yi-Cheng

2015-10-01

As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the Pearson correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

Linking Temperamental Shyness and Social Anxiety in Childhood and Adolescence: Moderating Influences of Sex and Age.

PubMed

Tsui, Tiffany Y L; Lahat, Ayelet; Schmidt, Louis A

2017-10-01

Although childhood shyness has been linked to social anxiety problems, the factors playing a role in this association have gone largely unexplored. Here we examined the potential moderating roles of sex and age on this relation in a sample of 119 (75 girls) children (10-12 years) and adolescents (14-16 years). As predicted, shyness was positively associated with social anxiety symptoms. Sex, but not age, served as a moderating factor in linking shyness and social anxiety. Specifically, shyness was more strongly associated with social anxiety symptoms among girls than boys. These results suggest the importance of considering sex differences when examining the relation between shyness and social anxiety in childhood and adolescence.

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

NASA Astrophysics Data System (ADS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

Early social networks predict survival in wild bottlenose dolphins.

PubMed

Stanton, Margaret A; Mann, Janet

2012-01-01

A fundamental question concerning group-living species is what factors influence the evolution of sociality. Although several studies link adult social bonds to fitness, social patterns and relationships are often formed early in life and are also likely to have fitness consequences, particularly in species with lengthy developmental periods, extensive social learning, and early social bond-formation. In a longitudinal study of bottlenose dolphins (Tursiops sp.), calf social network structure, specifically the metric eigenvector centrality, predicted juvenile survival in males. Additionally, male calves that died post-weaning had stronger ties to juvenile males than surviving male calves, suggesting that juvenile males impose fitness costs on their younger counterparts. Our study indicates that selection is acting on social traits early in life and highlights the need to examine the costs and benefits of social bonds during formative life history stages.

A comprehensive comparison of network similarities for link prediction and spurious link elimination

NASA Astrophysics Data System (ADS)

Zhang, Peng; Qiu, Dan; Zeng, An; Xiao, Jinghua

2018-06-01

Identifying missing interactions in complex networks, known as link prediction, is realized by estimating the likelihood of the existence of a link between two nodes according to the observed links and nodes' attributes. Similar approaches have also been employed to identify and remove spurious links in networks which is crucial for improving the reliability of network data. In network science, the likelihood for two nodes having a connection strongly depends on their structural similarity. The key to address these two problems thus becomes how to objectively measure the similarity between nodes in networks. In the literature, numerous network similarity metrics have been proposed and their accuracy has been discussed independently in previous works. In this paper, we systematically compare the accuracy of 18 similarity metrics in both link prediction and spurious link elimination when the observed networks are very sparse or consist of inaccurate linking information. Interestingly, some methods have high prediction accuracy, they tend to perform low accuracy in identification spurious interaction. We further find that methods can be classified into several cluster according to their behaviors. This work is useful for guiding future use of these similarity metrics for different purposes.

Community detection, link prediction, and layer interdependence in multilayer networks.

PubMed

De Bacco, Caterina; Power, Eleanor A; Larremore, Daniel B; Moore, Cristopher

2017-04-01

Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a mathematically principled way to define the interdependence between layers, by measuring how much information about one layer helps us predict links in another layer. In particular, this allows us to bundle layers together to compress redundant information and identify small groups of layers which suffice to predict the remaining layers accurately. We illustrate these findings by analyzing synthetic data and two real multilayer networks, one representing social support relationships among villagers in South India and the other representing shared genetic substring material between genes of the malaria parasite.

Community detection, link prediction, and layer interdependence in multilayer networks

NASA Astrophysics Data System (ADS)

De Bacco, Caterina; Power, Eleanor A.; Larremore, Daniel B.; Moore, Cristopher

2017-04-01

Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a mathematically principled way to define the interdependence between layers, by measuring how much information about one layer helps us predict links in another layer. In particular, this allows us to bundle layers together to compress redundant information and identify small groups of layers which suffice to predict the remaining layers accurately. We illustrate these findings by analyzing synthetic data and two real multilayer networks, one representing social support relationships among villagers in South India and the other representing shared genetic substring material between genes of the malaria parasite.

Social thermoregulation as a potential mechanism linking sociality and fitness: Barbary macaques with more social partners form larger huddles.

PubMed

Campbell, Liz A D; Tkaczynski, Patrick J; Lehmann, Julia; Mouna, Mohamed; Majolo, Bonaventura

2018-04-17

Individuals with more or stronger social bonds experience enhanced survival and reproduction in various species, though the mechanisms mediating these effects are unclear. Social thermoregulation is a common behaviour across many species which reduces cold stress exposure, body heat loss, and homeostatic energy costs, allowing greater energetic investment in growth, reproduction, and survival, with larger aggregations providing greater benefits. If more social individuals form larger thermoregulation aggregations due to having more potential partners, this would provide a direct link between sociality and fitness. We conducted the first test of this hypothesis by studying social relationships and winter sleeping huddles in wild Barbary macaques (Macaca sylvanus), wherein individuals with more social partners experience greater probability of winter survival. Precipitation and low temperature increased huddle sizes, supporting previous research that huddle size influences thermoregulation and energetics. Huddling relationships were predicted by social (grooming) relationships. Individuals with more social partners therefore formed larger huddles, suggesting reduced energy expenditure and exposure to environmental stressors than less social individuals, potentially explaining how sociality affects survival in this population. This is the first evidence that social thermoregulation may be a direct proximate mechanism by which increased sociality enhances fitness, which may be widely applicable across taxa.

Revealing how network structure affects accuracy of link prediction

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

PRELIM: Predictive Relevance Estimation from Linked Models

DTIC Science & Technology

2014-10-14

code ) 14-10-2014 Final Report 11-07-2014 to 14-10-2014 PRELIM: Predictive Relevance Estimation from Linked Models N00014-14-P-1185 10257H. Van Dyke...Parunak, Ph.D. Soar Technology, Inc. 1 Executive  Summary   PRELIM (Predictive Relevance Estimation from Linked Models) draws on semantic models...The central challenge in proactive decision support is to anticipate the decision and information needs of decision-makers, in the light of likely

Lateral orbitofrontal cortex links social impressions to political choices.

PubMed

Xia, Chenjie; Stolle, Dietlind; Gidengil, Elisabeth; Fellows, Lesley K

2015-06-03

Recent studies of political behavior suggest that voting decisions can be influenced substantially by "first-impression" social attributions based on physical appearance. Separate lines of research have implicated the orbitofrontal cortex (OFC) in the judgment of social traits on the one hand and economic decision-making on the other, making this region a plausible candidate for linking social attributions to voting decisions. Here, we asked whether OFC lesions in humans disrupted the ability to judge traits of political candidates or affected how these judgments influenced voting decisions. Seven patients with lateral OFC damage, 18 patients with frontal damage sparing the lateral OFC, and 53 matched healthy participants took part in a simulated election paradigm, in which they voted for real-life (but unknown) candidates based only on photographs of their faces. Consistent with previous work, attributions of "competence" and "attractiveness" based on candidate appearance predicted voting behavior in the healthy control group. Frontal damage did not affect substantially the ability to make competence or attractiveness judgments, but patients with damage to the lateral OFC differed from other groups in how they applied this information when voting. Only attractiveness ratings had any predictive power for voting choices after lateral OFC damage, whereas other frontal patients and healthy controls relied on information about both competence and attractiveness in making their choice. An intact lateral OFC may not be necessary for judgment of social traits based on physical appearance, but it seems to be crucial in applying this information in political decision-making. Copyright © 2015 the authors 0270-6474/15/358507-08$15.00/0.

Link prediction in the network of global virtual water trade

NASA Astrophysics Data System (ADS)

Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2016-04-01

Through the international food-trade, water resources are 'virtually' transferred from the country of production to the country of consumption. The international food-trade, thus, implies a network of virtual water flows from exporting to importing countries (i.e., nodes). Given the dynamical behavior of the network, where food-trade relations (i.e., links) are created and dismissed every year, link prediction becomes a challenge. In this study, we propose a novel methodology for link prediction in the virtual water network. The model aims at identifying the main factors (among 17 different variables) driving the creation of a food-trade relation between any two countries, along the period between 1986 and 2011. Furthermore, the model can be exploited to investigate the network configuration in the future, under different possible (climatic and demographic) scenarios. The model grounds the existence of a link between any two nodes on the link weight (i.e., the virtual water flow): a link exists when the nodes exchange a minimum (fixed) volume of virtual water. Starting from a set of potential links between any two nodes, we fit the associated virtual water flows (both the real and the null ones) by means of multivariate linear regressions. Then, links with estimated flows higher than a minimum value (i.e., threshold) are considered active-links, while the others are non-active ones. The discrimination between active and non-active links through the threshold introduces an error (called link-prediction error) because some real links are lost (i.e., missed links) and some non-existing links (i.e., spurious links) are inevitably introduced in the network. The major drivers are those significantly minimizing the link-prediction error. Once the structure of the unweighted virtual water network is known, we apply, again, linear regressions to assess the major factors driving the fluxes traded along (modelled) active-links. Results indicate that, on the one hand

Social Anxiety-Linked Attention Bias to Threat Is Indirectly Related to Post-Event Processing Via Subjective Emotional Reactivity to Social Stress.

PubMed

Çek, Demet; Sánchez, Alvaro; Timpano, Kiara R

2016-05-01

Attention bias to threat (e.g., disgust faces) is a cognitive vulnerability factor for social anxiety occurring in early stages of information processing. Few studies have investigated the relationship between social anxiety and attention biases, in conjunction with emotional and cognitive responses to a social stressor. Elucidating these links would shed light on maintenance factors of social anxiety and could help identify malleable treatment targets. This study examined the associations between social anxiety level, attention bias to disgust (AB-disgust), subjective emotional and physiological reactivity to a social stressor, and subsequent post-event processing (PEP). We tested a mediational model where social anxiety level indirectly predicted subsequent PEP via its association with AB-disgust and immediate subjective emotional reactivity to social stress. Fifty-five undergraduates (45% female) completed a passive viewing task. Eye movements were tracked during the presentation of social stimuli (e.g., disgust faces) and used to calculate AB-disgust. Next, participants gave an impromptu speech in front of a video camera and watched a neutral video, followed by the completion of a PEP measure. Although there was no association between AB-disgust and physiological reactivity to the stressor, AB-disgust was significantly associated with greater subjective emotional reactivity from baseline to the speech. Analyses supported a partial mediation model where AB-disgust and subjective emotional reactivity to a social stressor partially accounted for the link between social anxiety levels and PEP. Copyright © 2016. Published by Elsevier Ltd.

Influence of gender constancy and social power on sex-linked modeling.

PubMed

Bussey, K; Bandura, A

1984-12-01

Competing predictions derived from cognitive-developmental theory and social learning theory concerning sex-linked modeling were tested. In cognitive-developmental theory, gender constancy is considered a necessary prerequisite for the emulation of same-sex models, whereas according to social learning theory, sex-role development is promoted through a vast system of social influences with modeling serving as a major conveyor of sex role information. In accord with social learning theory, even children at a lower level of gender conception emulated same-sex models in preference to opposite-sex ones. Level of gender constancy was associated with higher emulation of both male and female models rather than operating as a selective determinant of modeling. This finding corroborates modeling as a basic mechanism in the sex-typing process. In a second experiment we explored the limits of same-sex modeling by pitting social power against the force of collective modeling of different patterns of behavior by male and female models. Social power over activities and rewarding resources produced cross-sex modeling in boys, but not in girls. This unexpected pattern of cross-sex modeling is explained by the differential sex-typing pressures that exist for boys and girls and socialization experiences that heighten the attractiveness of social power for boys.

Similarity indices based on link weight assignment for link prediction of unweighted complex networks

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-01-01

Many link prediction methods have been proposed for predicting the likelihood that a link exists between two nodes in complex networks. Among these methods, similarity indices are receiving close attention. Most similarity-based methods assume that the contribution of links with different topological structures is the same in the similarity calculations. This paper proposes a local weighted method, which weights the strength of connection between each pair of nodes. Based on the local weighted method, six local weighted similarity indices extended from unweighted similarity indices (including Common Neighbor (CN), Adamic-Adar (AA), Resource Allocation (RA), Salton, Jaccard and Local Path (LP) index) are proposed. Empirical study has shown that the local weighted method can significantly improve the prediction accuracy of these unweighted similarity indices and that in sparse and weakly clustered networks, the indices perform even better.

Link prediction based on local weighted paths for complex networks

NASA Astrophysics Data System (ADS)

Yao, Yabing; Zhang, Ruisheng; Yang, Fan; Yuan, Yongna; Hu, Rongjing; Zhao, Zhili

As a significant problem in complex networks, link prediction aims to find the missing and future links between two unconnected nodes by estimating the existence likelihood of potential links. It plays an important role in understanding the evolution mechanism of networks and has broad applications in practice. In order to improve prediction performance, a variety of structural similarity-based methods that rely on different topological features have been put forward. As one topological feature, the path information between node pairs is utilized to calculate the node similarity. However, many path-dependent methods neglect the different contributions of paths for a pair of nodes. In this paper, a local weighted path (LWP) index is proposed to differentiate the contributions between paths. The LWP index considers the effect of the link degrees of intermediate links and the connectivity influence of intermediate nodes on paths to quantify the path weight in the prediction procedure. The experimental results on 12 real-world networks show that the LWP index outperforms other seven prediction baselines.

A class-based link prediction using Distance Dependent Chinese Restaurant Process

NASA Astrophysics Data System (ADS)

Andalib, Azam; Babamir, Seyed Morteza

2016-08-01

One of the important tasks in relational data analysis is link prediction which has been successfully applied on many applications such as bioinformatics, information retrieval, etc. The link prediction is defined as predicting the existence or absence of edges between nodes of a network. In this paper, we propose a novel method for link prediction based on Distance Dependent Chinese Restaurant Process (DDCRP) model which enables us to utilize the information of the topological structure of the network such as shortest path and connectivity of the nodes. We also propose a new Gibbs sampling algorithm for computing the posterior distribution of the hidden variables based on the training data. Experimental results on three real-world datasets show the superiority of the proposed method over other probabilistic models for link prediction problem.

Early Adolescent Depressive Symptoms: Prediction from Clique Isolation, Loneliness, and Perceived Social Acceptance

PubMed Central

Witvliet, Miranda; Brendgen, Mara; van Lier, Pol A. C.; Vitaro, Frank

2010-01-01

This study examined whether clique isolation predicted an increase in depressive symptoms and whether this association was mediated by loneliness and perceived social acceptance in 310 children followed from age 11–14 years. Clique isolation was identified through social network analysis, whereas depressive symptoms, loneliness, and perceived social acceptance were assessed using self ratings. While accounting for initial levels of depressive symptoms, peer rejection, and friendlessness at age 11 years, a high probability of being isolated from cliques from age 11 to 13 years predicted depressive symptoms at age 14 years. The link between clique isolation and depressive symptoms was mediated by loneliness, but not by perceived social acceptance. No sex differences were found in the associations between clique isolation and depressive symptoms. These results suggest that clique isolation is a social risk factor for the escalation of depressive symptoms in early adolescence. Implications for research and prevention are discussed. PMID:20499155

Social Capital and Unretirement: Exploring the Bonding, Bridging, and Linking Aspects of Social Relationships.

PubMed

Gonzales, Ernest; Nowell, W Benjamin

2017-12-01

Working longer is an important area of research given extended life expectancy, shortfalls of retirement income, desires to remain socially engaged, and solvency concerns of social insurance programs. The purpose of this longitudinal population-based study of older adults is to examine how different types of social resources (social bonding, bridging, and linking) relate to returning to work after retirement. Data were drawn from the Health and Retirement Study of fully retired older adults aged 62+ in 1998 ( N = 8,334) and followed to 2008. After controlling for a comprehensive set of fixed and time-varying covariates, findings suggest that social bridging (informal volunteering) and social linking (formal volunteering, partnered with an employed spouse) were strongly and positively related to returning to work (Hazard Ratio [HR]: 1.49, p < .001; HR: 1.58, p < .0001; and HR: 1.75, p < .0001, respectively). Social bonding resources were not significantly associated with returning to work. Implications for social policy are discussed.

Encoded exposure to tobacco use in social media predicts subsequent smoking behavior.

PubMed

Depue, Jacob B; Southwell, Brian G; Betzner, Anne E; Walsh, Barbara M

2015-01-01

Assessing the potential link between smoking behavior and exposure to mass media depictions of smoking on social networking Web sites. A representative longitudinal panel of 200 young adults in Connecticut. Telephone surveys were conducted by using computer assisted telephone interviewing technology and electronic dialing for random digit dialing and listed samples. Connecticut residents aged 18 to 24 years. To measure encoded exposure, respondents were asked whether or not they had smoked a cigarette in the past 30 days and about how often they had seen tobacco use on television, in movies, and in social media content. Respondents were also asked about cigarette use in the past 30 days, and a series of additional questions that have been shown to be predictive of tobacco use. Logistic regression was used to test for our main prediction that reported exposure to social media tobacco depictions at time 1 would influence time 2 smoking behavior. Encoded exposure to social media tobacco depictions (B = .47, p < .05) was a significant predictor of time 2 smoking, even after controlling for all the aforementioned predictors. Our results suggest that social media depictions of tobacco use predict future smoking tendency, over and above the influence of TV and movie depictions of smoking. This is the first known study to specifically assess the role of social media in informing tobacco behavior.

A group evolving-based framework with perturbations for link prediction

NASA Astrophysics Data System (ADS)

Si, Cuiqi; Jiao, Licheng; Wu, Jianshe; Zhao, Jin

2017-06-01

Link prediction is a ubiquitous application in many fields which uses partially observed information to predict absence or presence of links between node pairs. The group evolving study provides reasonable explanations on the behaviors of nodes, relations between nodes and community formation in a network. Possible events in group evolution include continuing, growing, splitting, forming and so on. The changes discovered in networks are to some extent the result of these events. In this work, we present a group evolving-based characterization of node's behavioral patterns, and via which we can estimate the probability they tend to interact. In general, the primary aim of this paper is to offer a minimal toy model to detect missing links based on evolution of groups and give a simpler explanation on the rationality of the model. We first introduce perturbations into networks to obtain stable cluster structures, and the stable clusters determine the stability of each node. Then fluctuations, another node behavior, are assumed by the participation of each node to its own belonging group. Finally, we demonstrate that such characteristics allow us to predict link existence and propose a model for link prediction which outperforms many classical methods with a decreasing computational time in large scales. Encouraging experimental results obtained on real networks show that our approach can effectively predict missing links in network, and even when nearly 40% of the edges are missing, it also retains stationary performance.

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

Genetic Influences Can Protect Against Unresponsive Parenting in the Prediction of Child Social Competence

PubMed Central

Van Ryzin, Mark J.; Leve, Leslie D.; Neiderhiser, Jenae M.; Shaw, Daniel S.; Natsuaki, Misaki N.; Reiss, David

2014-01-01

Although social competence in children has been linked to the quality of parenting, prior research has typically not accounted for genetic similarities between parents and children, or for interactions between environmental (i.e., parental) and genetic influences. In this paper, we evaluate the possibility of a gene-by-environment (GxE) interaction in the prediction of social competence in school-age children. Using a longitudinal, multi-method dataset from a sample of children adopted at birth (N = 361), we found a significant interaction between birth parent sociability and sensitive, responsive adoptive parenting when predicting child social competence at school entry (age 6), even when controlling for potential confounds. An analysis of the interaction revealed that genetic strengths can buffer the effects of unresponsive parenting. PMID:25581124

Parental social anxiety disorder prospectively predicts toddlers' fear/avoidance in a social referencing paradigm.

PubMed

Aktar, Evin; Majdandžić, Mirjana; de Vente, Wieke; Bögels, Susan M

2014-01-01

Anxiety runs in families. Observational learning of anxious behavior from parents with anxiety disorders plays an important role in the intergenerational transmission of anxiety. We investigated the link between parental anxiety (parental lifetime anxiety disorders and expressed parental anxiety) and toddler fear/avoidance during social referencing (SR) situations. Toddlers (N = 117) participated with both parents (with lifetime social anxiety disorder, other nonsocial anxiety disorders, lifetime comorbid social and other anxiety disorders, or without anxiety disorders) in a longitudinal study. Behavioral inhibition (BI) was measured at 12 months via observational tasks. At 30 months, children were confronted with a stranger and a remote-control robot in SR situations, separately with each parent. Children's fear and avoidance, and parents' expressions of anxiety, encouragement, and overcontrol were observed. Toddlers of parents with lifetime social anxiety disorder (alone and comorbid with other anxiety disorders) showed more fear/avoidance in SR situations than toddlers of parents without anxiety disorders, while the effect of other anxiety disorders alone was not significant. Although expressed parental anxiety at 30 months in SR situations did not significantly predict toddlers' fear/avoidance, higher levels of expressed anxiety at 12 months in SR situations by parents with comorbid social and other anxiety disorders predicted higher levels of fear/avoidance. BI at 12 months predicted toddlers' fear/avoidance only with mothers, but not with fathers. Parental lifetime social anxiety disorders may be a stronger predictor of children's fear/avoidance than parents' expressions of anxiety in SR situations in toddlerhood. End of infancy may be a sensitive time for learning of anxiety from parents with comorbid lifetime social and nonsocial anxiety disorders in SR situations. Fathers are as important as mothers in the transmission of anxiety via SR. Furthermore

Variation in the X-Linked EFHC2 Gene Is Associated with Social Cognitive Abilities in Males

PubMed Central

Startin, Carla M.; Fiorentini, Chiara; de Haan, Michelle; Skuse, David H.

2015-01-01

Females outperform males on many social cognitive tasks. X-linked genes may contribute to this sex difference. Males possess one X chromosome, while females possess two X chromosomes. Functional variations in X-linked genes are therefore likely to impact more on males than females. Previous studies of X-monosomic women with Turner syndrome suggest a genetic association with facial fear recognition abilities at Xp11.3, specifically at a single nucleotide polymorphism (SNP rs7055196) within the EFHC2 gene. Based on a strong hypothesis, we investigated an association between variation at SNP rs7055196 and facial fear recognition and theory of mind abilities in males. As predicted, males possessing the G allele had significantly poorer facial fear detection accuracy and theory of mind abilities than males possessing the A allele (with SNP variant accounting for up to 4.6% of variance). Variation in the X-linked EFHC2 gene at SNP rs7055196 is therefore associated with social cognitive abilities in males. PMID:26107779

Link Prediction in Evolving Networks Based on Popularity of Nodes.

PubMed

Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian

2017-08-02

Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.

Neural responses to exclusion predict susceptibility to social influence.

PubMed

Falk, Emily B; Cascio, Christopher N; O'Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G

2014-05-01

Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American adolescents, traffic-related crashes are leading causes of nonfatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents' vulnerability to peer influence. We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately 1 week after the neuroimaging session. Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside the neuroimaging laboratory 1 week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. These results address the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging laboratory. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

Neural responses to exclusion predict susceptibility to social influence

PubMed Central

Falk, Emily B.; Cascio, Christopher N.; O’Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J.; Bingham, C. Raymond; Shope, Jean T.; Ouimet, Marie Claude; Pradhan, Anuj K.; Simons-Morton, Bruce G.

2014-01-01

Purpose Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence, and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American teens, traffic-related crashes are leading causes of non-fatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents’ vulnerability to peer influence. Methods We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently-licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately one week after the neuroimaging session. Results Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside of the neuroimaging lab one week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. Conclusions These results speak to the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging lab. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. PMID:24759437

Emotion dysregulation and social competence: stability, change and predictive power.

PubMed

Berkovits, L D; Baker, B L

2014-08-01

Social difficulties are closely linked to emotion dysregulation among children with typical development (TD). Children with developmental delays (DD) are at risk for poor social outcomes, but the relationship between social and emotional development within this population is not well understood. The current study examines the extent to which emotion dysregulation is related to social problems across middle childhood among children with TD or DD. Children with TD (IQ ≥ 85, n = 113) and children with DD (IQ ≤ 75, n = 61) participated in a longitudinal study. Annual assessments were completed at ages 7, 8 and 9 years. At each assessment, mothers reported on children's emotion dysregulation, and both mothers and teachers reported on children's social difficulties. Children with DD had higher levels of emotion dysregulation and social problems at each age than those with TD. Emotion dysregulation and social problems were significantly positively correlated within both TD and DD groups using mother report of social problems, and within the TD group using teacher report of social problems. Among children with TD, emotion dysregulation consistently predicted change in social problems from one year to the next. However, among children with DD, emotion dysregulation offered no unique prediction value above and beyond current social problems. Results suggested that the influence of emotion regulation abilities on social development may be a less salient pathway for children with DD. These children may have more influences, beyond emotion regulation, on their social behaviour, highlighting the importance of directly targeting social skill deficits among children with DD in order to ameliorate their social difficulties. © 2013 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

The role of social relationships in the link between olfactory dysfunction and mortality.

PubMed

Leschak, Carrianne J; Eisenberger, Naomi I

2018-01-01

Recent work suggests that olfactory dysfunction is a strong predictor of five-year mortality in older adults. Based on past work showing: 1) that olfactory dysfunction impairs social functioning and 2) that social ties are linked with mortality, the current work explored whether impairments in social life mediated the relationship between olfactory dysfunction and mortality. Additionally, based on work showing gender differences in the social consequences of olfactory dysfunction, gender was assessed as a potential moderator of this association. Social network size mediated the olfactory-mortality link for females. To probe what feature of social networks was driving this effect, we investigated two subcomponents of social life: emotional closeness (e.g., perceived social support, loneliness) and physical closeness (e.g., physical contact, in-person socializing with others). Physical closeness significantly mediated the olfactory-mortality link for females, even after controlling for social network size. Emotional closeness did not mediate this link. Possible mechanisms underlying this relationship are discussed.

An auxiliary optimization method for complex public transit route network based on link prediction

NASA Astrophysics Data System (ADS)

Zhang, Lin; Lu, Jian; Yue, Xianfei; Zhou, Jialin; Li, Yunxuan; Wan, Qian

2018-02-01

Inspired by the missing (new) link prediction and the spurious existing link identification in link prediction theory, this paper establishes an auxiliary optimization method for public transit route network (PTRN) based on link prediction. First, link prediction applied to PTRN is described, and based on reviewing the previous studies, the summary indices set and its algorithms set are collected for the link prediction experiment. Second, through analyzing the topological properties of Jinan’s PTRN established by the Space R method, we found that this is a typical small-world network with a relatively large average clustering coefficient. This phenomenon indicates that the structural similarity-based link prediction will show a good performance in this network. Then, based on the link prediction experiment of the summary indices set, three indices with maximum accuracy are selected for auxiliary optimization of Jinan’s PTRN. Furthermore, these link prediction results show that the overall layout of Jinan’s PTRN is stable and orderly, except for a partial area that requires optimization and reconstruction. The above pattern conforms to the general pattern of the optimal development stage of PTRN in China. Finally, based on the missing (new) link prediction and the spurious existing link identification, we propose optimization schemes that can be used not only to optimize current PTRN but also to evaluate PTRN planning.

Psychosocial Mechanisms Linking the Social Environment to Mental Health in African Americans.

PubMed

Mama, Scherezade K; Li, Yisheng; Basen-Engquist, Karen; Lee, Rebecca E; Thompson, Deborah; Wetter, David W; Nguyen, Nga T; Reitzel, Lorraine R; McNeill, Lorna H

2016-01-01

Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African American adults. African American men and women (n = 1467) completed questionnaires on the social environment, psychosocial factors (stress, depressive symptoms, and racial discrimination), and mental health. Multiple-mediator models were used to assess direct and indirect effects of the social environment on mental health. Low social status in the community (p < .001) and U.S. (p < .001) and low social support (p < .001) were associated with poor mental health. Psychosocial factors significantly jointly mediated the relationship between the social environment and mental health in multiple-mediator models. Low social status and social support were associated with greater perceived stress, depressive symptoms, and perceived racial discrimination, which were associated with poor mental health. Results suggest the relationship between the social environment and mental health is mediated by psychosocial factors and revealed potential mechanisms through which social status and social support influence the mental health of African American men and women. Findings from this study provide insight into the differential effects of stress, depression and discrimination on mental health. Ecological approaches that aim to improve the social environment and psychosocial mediators may enhance health-related quality of life and reduce health disparities in African Americans.

Psychosocial Mechanisms Linking the Social Environment to Mental Health in African Americans

PubMed Central

Basen-Engquist, Karen; Lee, Rebecca E.; Thompson, Deborah; Wetter, David W.; Reitzel, Lorraine R.

2016-01-01

Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African American adults. African American men and women (n = 1467) completed questionnaires on the social environment, psychosocial factors (stress, depressive symptoms, and racial discrimination), and mental health. Multiple-mediator models were used to assess direct and indirect effects of the social environment on mental health. Low social status in the community (p < .001) and U.S. (p < .001) and low social support (p < .001) were associated with poor mental health. Psychosocial factors significantly jointly mediated the relationship between the social environment and mental health in multiple-mediator models. Low social status and social support were associated with greater perceived stress, depressive symptoms, and perceived racial discrimination, which were associated with poor mental health. Results suggest the relationship between the social environment and mental health is mediated by psychosocial factors and revealed potential mechanisms through which social status and social support influence the mental health of African American men and women. Findings from this study provide insight into the differential effects of stress, depression and discrimination on mental health. Ecological approaches that aim to improve the social environment and psychosocial mediators may enhance health-related quality of life and reduce health disparities in African Americans. PMID:27119366

The missing link: leadership, identity, and the social brain.

PubMed

van Vugt, Mark

2012-05-01

How the cohesion of a social network is being maintained in spite of having different layers of social interaction is an important question. I argue that the evolution of both (political) hierarchy and social identity play a crucial role in scaling up and bonding social networks. Together they are missing links in the social brain hypothesis, and further research is needed to understand the functions of leadership and social identity. ©2011 The British Psychological Society.

Retweets as a Predictor of Relationships among Users on Social Media.

PubMed

Tsugawa, Sho; Kito, Kosuke

2017-01-01

Link prediction is the problem of detecting missing links or predicting future link formation in a network. Application of link prediction to social media, such as Twitter and Facebook, is useful both for developing novel services and for sociological analyses. While most existing research on link prediction uses only the social network topology for the prediction, in social media, records of user activities such as posting, replying, and reposting are available. These records are expected to reflect user interest, and so incorporating them should improve link prediction. However, research into link prediction using the records of user activities is still in its infancy, and the effectiveness of such records for link prediction has not been fully explored. In this study, we focus in particular on records of reposting as a promising source that could be useful for link prediction, and investigate their effectiveness for link prediction on the popular social media platform Twitter. Our results show that (1) the prediction accuracy of techniques using reposting records is higher than that of popular topology-based techniques such as common neighbors and resource allocation for actively retweeting users, (2) the accuracy of link prediction techniques that use network topology alone can be improved by incorporating reposting records.

Retweets as a Predictor of Relationships among Users on Social Media

PubMed Central

Kito, Kosuke

2017-01-01

Link prediction is the problem of detecting missing links or predicting future link formation in a network. Application of link prediction to social media, such as Twitter and Facebook, is useful both for developing novel services and for sociological analyses. While most existing research on link prediction uses only the social network topology for the prediction, in social media, records of user activities such as posting, replying, and reposting are available. These records are expected to reflect user interest, and so incorporating them should improve link prediction. However, research into link prediction using the records of user activities is still in its infancy, and the effectiveness of such records for link prediction has not been fully explored. In this study, we focus in particular on records of reposting as a promising source that could be useful for link prediction, and investigate their effectiveness for link prediction on the popular social media platform Twitter. Our results show that (1) the prediction accuracy of techniques using reposting records is higher than that of popular topology-based techniques such as common neighbors and resource allocation for actively retweeting users, (2) the accuracy of link prediction techniques that use network topology alone can be improved by incorporating reposting records. PMID:28107489

Preserving and maintaining vital Ecosystem Services: the importance of linking knowledge from Geosciences and social-ecological System analysis

NASA Astrophysics Data System (ADS)

Finger, David; Petursdottir, Thorunn

2013-04-01

Human kind has always been curios and motivated to understand and quantify environmental processes in order to predict and anticipate the evolution of vital ecosystem services. Even the very first civilizations used empirical correlations to predict outcomes of rains and subsequent harvest efficiencies. Along with the insights into the functioning of ecosystems, humans also became aware that their anthropogenic activities can have positive and negative impact on ecosystem services. In recent years, geosciences have brought forward new sophisticated observations and modeling tools, with the aim to improve predictions of ecological developments. At the same time, the added value of linking ecological factors to the surrounding social structure has received a growing acceptance among scientists. A social-ecological system approach brings in a holistic understanding of how these systems are inevitably interlinked and how their sustainability can be better maintained. We claim that the biggest challenge for geoscience in the coming decades will be to link these two disciplines in order to establish adequate strategies to preserve natural ecosystems and their services, parallel to their utilization. We will present various case studies from more than a decade of research, ranging from water quality in mountain lakes, climate change impacts on water availability and declining fishing yields in freshwaters and discuss how the studies outcomes could be given added value by interpreting them via social-ecological system analysis. For instance, sophisticated field investigations revealed that deep water mixing in lake Issyk-Kul, Kirgizstan, is intensively distributing pollutants in the entire lake. Although fishery is an important sector in the region, the local awareness of the importance of water quality is low. In Switzerland, strict water protection laws led to ologotrophication of alpine lakes, reducing fishing yields. While local fishermen argued that local fishery is

PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

PubMed

Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

2016-01-01

We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

Link prediction based on nonequilibrium cooperation effect

NASA Astrophysics Data System (ADS)

Li, Lanxi; Zhu, Xuzhen; Tian, Hui

2018-04-01

Link prediction in complex networks has become a common focus of many researchers. But most existing methods concentrate on neighbors, and rarely consider degree heterogeneity of two endpoints. Node degree represents the importance or status of endpoints. We describe the large-degree heterogeneity as the nonequilibrium between nodes. This nonequilibrium facilitates a stable cooperation between endpoints, so that two endpoints with large-degree heterogeneity tend to connect stably. We name such a phenomenon as the nonequilibrium cooperation effect. Therefore, this paper proposes a link prediction method based on the nonequilibrium cooperation effect to improve accuracy. Theoretical analysis will be processed in advance, and at the end, experiments will be performed in 12 real-world networks to compare the mainstream methods with our indices in the network through numerical analysis.

Personality and prosocial behavior: linking basic traits and social value orientations.

PubMed

Hilbig, Benjamin E; Glöckner, Andreas; Zettler, Ingo

2014-09-01

Concerning the dispositional determinants of prosocial behavior and cooperation, work based on the classic 5 personality factors, and especially Agreeableness, has turned out somewhat inconsistent. A clearer picture has emerged from consideration of the HEXACO model of personality--though supported entirely by hypothetical behavior as criterion, so far. Thus, in 2 studies and a reanalysis, we investigated "actual behavior" in the form of individually and socially consequential distribution decisions. As expected, HEXACO Honesty-Humility consistently predicted prosocial behavior, including a theory-consistent pattern on the facet level. Importantly, this pattern might explain why five-factor Agreeableness has only sometimes been found to account for prosocial behavior. Indeed, further results indicate that five-factor Agreeableness comprises some aspects that are predictive of prosocial behavior--aspects well covered by HEXACO Honesty-Humility--but also others that play no role for this criterion. As such, the links between five-factor Agreeableness and prosocial behavior are well-covered by HEXACO Honesty-Humility, but not vice versa. Taken together, these findings hint that especially HEXACO Honesty-Humility (and certain aspects of five-factor Agreeableness) account for prosocial behavior--thus explaining previous inconsistencies and providing a more nuanced understanding of the links between basic personality and prosocial or cooperative behavior. 2014 APA, all rights reserved

Statistical similarity measures for link prediction in heterogeneous complex networks

NASA Astrophysics Data System (ADS)

Shakibian, Hadi; Charkari, Nasrollah Moghadam

2018-07-01

The majority of the link prediction measures in heterogeneous complex networks rely on the nodes connectivities while less attention has been paid to the importance of the nodes and paths. In this paper, we propose some new meta-path based statistical similarity measures to properly perform link prediction task. The main idea in the proposed measures is to drive some co-occurrence events in a number of co-occurrence matrices that are occurred between the visited nodes obeying a meta-path. The extracted co-occurrence matrices are analyzed in terms of the energy, inertia, local homogeneity, correlation, and information measure of correlation to determine various information theoretic measures. We evaluate the proposed measures, denoted as link energy, link inertia, link local homogeneity, link correlation, and link information measure of correlation, using a standard DBLP network data set. The results of the AUC score and Precision rate indicate the validity and accuracy of the proposed measures in comparison to the popular meta-path based similarity measures.

Entropy-based link prediction in weighted networks

NASA Astrophysics Data System (ADS)

Xu, Zhongqi; Pu, Cunlai; Ramiz Sharafat, Rajput; Li, Lunbo; Yang, Jian

2017-01-01

Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks. In the previous work (Xu et al, 2016 \\cite{xu2016}), we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight, and propose a weighted prediction index based on the contributions of paths, namely Weighted Path Entropy (WPE), to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three typical weighted indices.

Understanding social anxiety as a risk for alcohol use disorders: Fear of scrutiny, not social interaction fears, prospectively predicts alcohol use disorders

PubMed Central

Buckner, Julia D.; Schmidt, Norman B.

2009-01-01

Increasing evidence indicates that social anxiety may be a premorbid risk factor for alcohol use disorders (AUD). The aim of this study was to replicate and extend previous work examining whether social anxiety is a risk factor for AUD by evaluating both the temporal antecedence and non-spuriousness of this relationship. We also examined whether social anxiety first-order factors (social interaction anxiety, observation anxieties) served as specific predictors of AUD. A non-referred sample of 404 psychologically healthy young adults (i.e. free from current or past Axis I psychopathology) was prospectively followed over approximately two years. Social anxiety (but not depression or trait anxiety) at baseline significantly predicted subsequent AUD onset. The relationship between social anxiety and AUD remained even after controlling for relevant variables (gender, depression, trait anxiety). Further, social anxiety first-order factors differentially predicted AUD onset, such that observation anxieties (but not social interaction anxiety) were prospectively linked to AUD onset. This study provides further support that social anxiety (and fear of scrutiny specifically) appears to serve as an important and potentially specific AUD-related variable that deserves serious attention as a potential vulnerability factor. PMID:18547587

Linking social capital and mortality in the elderly: a Swedish national cohort study.

PubMed

Sundquist, Kristina; Hamano, Tsuyoshi; Li, Xinjun; Kawakami, Naomi; Shiwaku, Kuninori; Sundquist, Jan

2014-07-01

Our objective was to examine the association between neighborhood linking social capital (a concept describing the amount of trust between individuals and societal institutions) and all-cause and cause-specific mortality in the elderly. The entire Swedish population aged 65+, a total of 1,517,336 men and women, was followed from 1 January 2002 until death, emigration, or the end of the study on 31 December 2010. Small geographic units were used to define neighborhoods. The definition of linking social capital was based on neighborhood voting participation rates, categorized into three groups. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance in three different models. The results showed an overall association between linking social capital and all-cause mortality. The significant OR of 1.53 in the group with low linking social capital decreased, but remained significant (OR=1.27), after accounting for age, sex, family income, marital status, country of birth, education level, and region of residence. There were also significant associations between linking social capital and cause-specific mortality in coronary heart disease, psychiatric disorders, cancer, stroke, chronic lower respiratory diseases, type 2 diabetes, and suicide. There are associations between low linking social capital and mortality from chronic disorders and suicide in the elderly population. Community support for elderly people living in neighborhoods with low levels of linking social capital may need to be strengthened. Copyright © 2014 Elsevier Inc. All rights reserved.

Processes Linking Social Class and Racial Socialization in African American Dual-Earner Families

ERIC Educational Resources Information Center

Crouter, Ann C.; Baril, Megan E.; Davis, Kelly D.; McHale, Susan M.

2008-01-01

We examined the links between social class, occupational self-direction, self-efficacy, and racial socialization in a sample of 128 two-parent African American couples raising adolescents. A series of multivariate, multilevel models revealed that mothers' SES was connected to self-efficacy via its association with occupational self-direction; in…

Genetic influences can protect against unresponsive parenting in the prediction of child social competence.

PubMed

Van Ryzin, Mark J; Leve, Leslie D; Neiderhiser, Jenae M; Shaw, Daniel S; Natsuaki, Misaki N; Reiss, David

2015-01-01

Although social competence in children has been linked to the quality of parenting, prior research has typically not accounted for genetic similarities between parents and children, or for interactions between environmental (i.e., parental) and genetic influences. In this article, the possibility of a Gene x Environment (G × E) interaction in the prediction of social competence in school-age children is evaluated. Using a longitudinal, multimethod data set from a sample of children adopted at birth (N = 361), a significant interaction was found between birth parent sociability and sensitive, responsive adoptive parenting when predicting child social competence at school entry (age 6), even when controlling for potential confounds. An analysis of the interaction revealed that genetic strengths can buffer the effects of unresponsive parenting. © 2015 The Authors. Child Development © 2015 Society for Research in Child Development, Inc.

Predicting the social consequences of orphanhood in South Africa.

PubMed

Bray, Rachel

2003-01-01

This paper examines and questions the predictions found in the academic and policy literature of social breakdown in southern Africa in the wake of anticipated high rates of orphanhood caused by the AIDS epidemic. Analysis of the logic underlying these predictions reveals four causal relationships necessary to fulfil such dramatic and apocalyptic predictions: High AIDS mortality rates will produce high numbers of orphans. These orphans will become children who do not live in appropriate social environments to equip them for adult citizenship. Poor socialisation will mean that children orphaned by AIDS will not live within society's moral codes (becoming, for example, street children or juvenile delinquents). Large numbers of such 'asocial' or 'antisocial' children will precipitate a breakdown in the social fabric. Evidence for each of these steps in the argument is scrutinised using available data from southern Africa and other regions that have moved further through the epidemic's cycle. The paper finds strong evidence for the first step, although variable definitions of 'orphan' make it difficult to draw accurate comparisons over time and space. Evidence for the second step is found to be mixed in terms of outcomes of AIDS orphanhood for child well-being. Moreover the argument takes little account of the social and economic environments onto which AIDS is mapped, including the economic fragility of households and pervading socio-cultural patterns of child-rearing. Data to substantiate the third step are anecdotal at best and no research is able to demonstrate a link between the long term effects of AIDS orphanhood and rising rates of juvenile delinquency. Arguments made towards the fourth step are shown to be based heavily on notions of the 'correct' social and physical environments for children and on unsubstantiated fears of alternatives to these. There is no evidence from countries where numbers of AIDS orphans are already high to suggest that their presence

Efficient network disintegration under incomplete information: the comic effect of link prediction

NASA Astrophysics Data System (ADS)

Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

2016-03-01

The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

Efficient network disintegration under incomplete information: the comic effect of link prediction.

PubMed

Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

2016-03-10

The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the "comic effect" of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

Efficient network disintegration under incomplete information: the comic effect of link prediction

PubMed Central

Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

2016-01-01

The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized. PMID:26960247

Perceived social support predicts increased conscientiousness during older adulthood.

PubMed

Hill, Patrick L; Payne, Brennan R; Jackson, Joshua J; Stine-Morrow, Elizabeth A L; Roberts, Brent W

2014-07-01

This study examined whether perceived social support predicted adaptive personality change in older adulthood, focusing on the trait of conscientiousness. We tested this hypothesis both at the broad domain level and with respect to the specific lower order facets that comprise conscientiousness: order, self-control, industriousness, responsibility, and traditionalism. A sample of 143 older adults (aged 60-91) completed measures of conscientiousness and social support during 2 assessments 7 months apart. Social support and conscientiousness were positively correlated among older adults. Moreover, older adults who perceived greater social support at baseline were more likely to gain in conscientiousness over time. The magnitude of this effect was relatively similar across the order, self-control, and industriousness facets. Perceived social support provides multiple benefits later in life, and the current results add to this literature by showing that it also promotes conscientiousness. As conscientiousness is linked to a variety of positive outcomes later in life, including health, future research should examine whether conscientiousness change may be an important mechanism through which social support enhances resilience in older adulthood. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Predicting the Trends of Social Events on Chinese Social Media.

PubMed

Zhou, Yang; Zhang, Lei; Liu, Xiaoqian; Zhang, Zhen; Bai, Shuotian; Zhu, Tingshao

2017-09-01

Growing interest in social events on social media came along with the rapid development of the Internet. Social events that occur in the "real" world can spread on social media (e.g., Sina Weibo) rapidly, which may trigger severe consequences and thus require the government's timely attention and responses. This article proposes to predict the trends of social events on Sina Weibo, which is currently the most popular social media in China. Based on the theories of social psychology and communication sciences, we extract an unprecedented amount of comprehensive and effective features that relate to the trends of social events on Chinese social media, and we construct the trends of prediction models by using three classical regression algorithms. We found that lasso regression performed better with the precision 0.78 and the recall 0.88. The results of our experiments demonstrated the effectiveness of our proposed approach.

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

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

Zhang, Baichuan; Choudhury, Sutanay; Al-Hasan, Mohammad

2016-02-01

Estimating the confidence for a link is a critical task for Knowledge Graph construction. Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area. We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate. Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches. Furthermore, we also study the performance of the link prediction algorithm in termsmore » of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy.« less

A link prediction method for heterogeneous networks based on BP neural network

NASA Astrophysics Data System (ADS)

Li, Ji-chao; Zhao, Dan-ling; Ge, Bing-Feng; Yang, Ke-Wei; Chen, Ying-Wu

2018-04-01

Most real-world systems, composed of different types of objects connected via many interconnections, can be abstracted as various complex heterogeneous networks. Link prediction for heterogeneous networks is of great significance for mining missing links and reconfiguring networks according to observed information, with considerable applications in, for example, friend and location recommendations and disease-gene candidate detection. In this paper, we put forward a novel integrated framework, called MPBP (Meta-Path feature-based BP neural network model), to predict multiple types of links for heterogeneous networks. More specifically, the concept of meta-path is introduced, followed by the extraction of meta-path features for heterogeneous networks. Next, based on the extracted meta-path features, a supervised link prediction model is built with a three-layer BP neural network. Then, the solution algorithm of the proposed link prediction model is put forward to obtain predicted results by iteratively training the network. Last, numerical experiments on the dataset of examples of a gene-disease network and a combat network are conducted to verify the effectiveness and feasibility of the proposed MPBP. It shows that the MPBP with very good performance is superior to the baseline methods.

Predicting missing links in complex networks based on common neighbors and distance

PubMed Central

Yang, Jinxuan; Zhang, Xiao-Dong

2016-01-01

The algorithms based on common neighbors metric to predict missing links in complex networks are very popular, but most of these algorithms do not account for missing links between nodes with no common neighbors. It is not accurate enough to reconstruct networks by using these methods in some cases especially when between nodes have less common neighbors. We proposed in this paper a new algorithm based on common neighbors and distance to improve accuracy of link prediction. Our proposed algorithm makes remarkable effect in predicting the missing links between nodes with no common neighbors and performs better than most existing currently used methods for a variety of real-world networks without increasing complexity. PMID:27905526

A Neurobehavioral Mechanism Linking Behaviorally Inhibited Temperament and Later Adolescent Social Anxiety.

PubMed

Buzzell, George A; Troller-Renfree, Sonya V; Barker, Tyson V; Bowman, Lindsay C; Chronis-Tuscano, Andrea; Henderson, Heather A; Kagan, Jerome; Pine, Daniel S; Fox, Nathan A

2017-12-01

Behavioral inhibition (BI) is a temperament identified in early childhood that is a risk factor for later social anxiety. However, mechanisms underlying the development of social anxiety remain unclear. To better understand the emergence of social anxiety, longitudinal studies investigating changes at behavioral neural levels are needed. BI was assessed in the laboratory at 2 and 3 years of age (N = 268). Children returned at 12 years, and an electroencephalogram was recorded while children performed a flanker task under 2 conditions: once while believing they were being observed by peers and once while not being observed. This methodology isolated changes in error monitoring (error-related negativity) and behavior (post-error reaction time slowing) as a function of social context. At 12 years, current social anxiety symptoms and lifetime diagnoses of social anxiety were obtained. Childhood BI prospectively predicted social-specific error-related negativity increases and social anxiety symptoms in adolescence; these symptoms directly related to clinical diagnoses. Serial mediation analysis showed that social error-related negativity changes explained relations between BI and social anxiety symptoms (n = 107) and diagnosis (n = 92), but only insofar as social context also led to increased post-error reaction time slowing (a measure of error preoccupation); this model was not significantly related to generalized anxiety. Results extend prior work on socially induced changes in error monitoring and error preoccupation. These measures could index a neurobehavioral mechanism linking BI to adolescent social anxiety symptoms and diagnosis. This mechanism could relate more strongly to social than to generalized anxiety in the peri-adolescent period. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. All rights reserved.

Health Communication in Social Media: Message Features Predicting User Engagement on Diabetes-Related Facebook Pages.

PubMed

Rus, Holly M; Cameron, Linda D

2016-10-01

Social media provides unprecedented opportunities for enhancing health communication and health care, including self-management of chronic conditions such as diabetes. Creating messages that engage users is critical for enhancing message impact and dissemination. This study analyzed health communications within ten diabetes-related Facebook pages to identify message features predictive of user engagement. The Common-Sense Model of Illness Self-Regulation and established health communication techniques guided content analyses of 500 Facebook posts. Each post was coded for message features predicted to engage users and numbers of likes, shares, and comments during the week following posting. Multi-level, negative binomial regressions revealed that specific features predicted different forms of engagement. Imagery emerged as a strong predictor; messages with images had higher rates of liking and sharing relative to messages without images. Diabetes consequence information and positive identity predicted higher sharing while negative affect, social support, and crowdsourcing predicted higher commenting. Negative affect, crowdsourcing, and use of external links predicted lower sharing while positive identity predicted lower commenting. The presence of imagery weakened or reversed the positive relationships of several message features with engagement. Diabetes control information and negative affect predicted more likes in text-only messages, but fewer likes when these messages included illustrative imagery. Similar patterns of imagery's attenuating effects emerged for the positive relationships of consequence information, control information, and positive identity with shares and for positive relationships of negative affect and social support with comments. These findings hold promise for guiding communication design in health-related social media.

To trade or not to trade: Link prediction in the virtual water network

NASA Astrophysics Data System (ADS)

Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2017-12-01

In the international trade network, links express the (temporary) presence of a commercial exchange of goods between any two countries. Given the dynamical behaviour of the trade network, where links are created and dismissed every year, predicting the link activation/deactivation is an open research question. Through the international trade network of agricultural goods, water resources are 'virtually' transferred from the country of production to the country of consumption. We propose a novel methodology for link prediction applied to the network of virtual water trade. Starting from the assumption of having links between any two countries, we estimate the associated virtual water flows by means of a gravity-law model using country and link characteristics as drivers. We consider the links with estimated flows higher than 1000 m3/year as active links, while the others as non-active links. Flows traded along estimated active links are then re-estimated using a similar but differently-calibrated gravity-law model. We were able to correctly model 84% of the existing links and 93% of the non-existing links in year 2011. It is worth to note that the predicted active links carry 99% of the global virtual water flow; hence, missed links are mainly those where a minimum volume of virtual water is exchanged. Results indicate that, over the period from 1986 to 2011, population, geographical distances between countries, and agricultural efficiency (through fertilizers use) are the major factors driving the link activation and deactivation. As opposed to other (network-based) models for link prediction, the proposed method is able to reconstruct the network architecture without any prior knowledge of the network topology, using only the nodes and links attributes; it thus represents a general method that can be applied to other networks such as food or value trade networks.

Toward Predicting Social Support Needs in Online Health Social Networks.

PubMed

Choi, Min-Je; Kim, Sung-Hee; Lee, Sukwon; Kwon, Bum Chul; Yi, Ji Soo; Choo, Jaegul; Huh, Jina

2017-08-02

While online health social networks (OHSNs) serve as an effective platform for patients to fulfill their various social support needs, predicting the needs of users and providing tailored information remains a challenge. The objective of this study was to discriminate important features for identifying users' social support needs based on knowledge gathered from survey data. This study also provides guidelines for a technical framework, which can be used to predict users' social support needs based on raw data collected from OHSNs. We initially conducted a Web-based survey with 184 OHSN users. From this survey data, we extracted 34 features based on 5 categories: (1) demographics, (2) reading behavior, (3) posting behavior, (4) perceived roles in OHSNs, and (5) values sought in OHSNs. Features from the first 4 categories were used as variables for binary classification. For the prediction outcomes, we used features from the last category: the needs for emotional support, experience-based information, unconventional information, and medical facts. We compared 5 binary classifier algorithms: gradient boosting tree, random forest, decision tree, support vector machines, and logistic regression. We then calculated the scores of the area under the receiver operating characteristic (ROC) curve (AUC) to understand the comparative effectiveness of the used features. The best performance was AUC scores of 0.89 for predicting users seeking emotional support, 0.86 for experience-based information, 0.80 for unconventional information, and 0.83 for medical facts. With the gradient boosting tree as our best performing model, we analyzed the strength of individual features in predicting one's social support need. Among other discoveries, we found that users seeking emotional support tend to post more in OHSNs compared with others. We developed an initial framework for automatically predicting social support needs in OHSNs using survey data. Future work should involve nonsurvey

Social Trust Prediction Using Heterogeneous Networks.

PubMed

Huang, Jin; Nie, Feiping; Huang, Heng; Tu, Yi-Cheng; Lei, Yu

2013-11-01

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method.

Social Trust Prediction Using Heterogeneous Networks

PubMed Central

HUANG, JIN; NIE, FEIPING; HUANG, HENG; TU, YI-CHENG; LEI, YU

2014-01-01

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method. PMID:24729776

Antiretroviral drug diversion links social vulnerability to poor medication adherence in substance abusing populations.

PubMed

Tsuyuki, Kiyomi; Surratt, Hilary L

2015-05-01

Antiretroviral (ARV) medication diversion to the illicit market has been documented in South Florida, and linked to sub-optimal adherence in people living with HIV. ARV diversion reflects an unmet need for care in vulnerable populations that have difficulty engaging in consistent HIV care due to competing needs and co-morbidities. This study applies the Gelberg-Andersen behavioral model of health care utilization for vulnerable populations to understand how social vulnerability is linked to ARV diversion and adherence. Cross-sectional data were collected from a targeted sample of vulnerable people living with HIV in South Florida between 2010 and 2012 (n = 503). Structured interviews collected quantitative data on ARV diversion, access and utilization of care, and ARV adherence. Logistic regression was used to estimate the goodness-of-fit of additive models that test domain fit. Linear regression was used to estimate the effects of social vulnerability and ARV diversion on ARV adherence. The best fitting model to predict ARV diversion identifies having a low monthly income and unstable HIV care as salient enabling factors that promote ARV diversion. Importantly, health care need factors did not protect against ARV diversion, evidence that immediate competing needs are prioritized even in the face of poor health for this sample. We also find that ARV diversion provides a link between social vulnerability and sub-optimal ARV adherence, with ARV diversion and domains from the Behavioral Model explaining 25 % of the variation in ARV adherence. Our analyses reveal great need to improve engagement in HIV care for vulnerable populations by strengthening enabling factors (e.g. patient-provider relationship) to improve retention in HIV care and ARV adherence for vulnerable populations.

Neuronal activity in primate dorsal anterior cingulate cortex signals task conflict and predicts adjustments in pupil-linked arousal

PubMed Central

Ebitz, R. Becket; Platt, Michael L.

2014-01-01

Summary Whether driving a car, shopping for food, or paying attention in a classroom of boisterous teenagers, it’s often hard to maintain focus on goals in the face of distraction. Brain imaging studies in humans implicate the dorsal anterior cingulate cortex (dACC) in regulating the conflict between goals and distractors. Here we show for the first time that single dACC neurons signal conflict between task goals and distractors in the rhesus macaque, particularly for biologically-relevant social stimuli. For some neurons, task conflict signals predicted subsequent changes in pupil size—a peripheral index of arousal linked to noradrenergic tone—associated with reduced distractor interference. dACC neurons also responded to errors and these signals predicted adjustments in pupil size. These findings provide the first neurophysiological endorsement of the hypothesis that dACC regulates conflict, in part, via modulation of pupil-linked processes such as arousal. PMID:25654259

Linking information and people in a social system for academic conferences

NASA Astrophysics Data System (ADS)

Brusilovsky, Peter; Oh, Jung Sun; López, Claudia; Parra, Denis; Jeng, Wei

2017-04-01

This paper investigates the feasibility of maintaining a social information system to support attendees at an academic conference. The main challenge of this work was to create an infrastructure where users' social activities, such as bookmarking, tagging, and social linking could be used to enhance user navigation and maximize the users' ability to locate two important types of information in conference settings: presentations to attend and attendees to meet. We developed Conference Navigator 3, a social conference support system that integrates a conference schedule planner with a social linking service. We examined its potential and functions in the context of a medium-scale academic conference. In this paper, we present the design of the system's socially enabled features and report the results of a conference-based study. Our study demonstrates the feasibility of social information systems for supporting academic conferences. Despite the low number of potential users and the short timeframe in which conferences took place, the usage of the system was high enough to provide sufficient data for social mechanisms. The study shows that most critical social features were highly appreciated and used, and provides direction for further research.

Biomine: predicting links between biological entities using network models of heterogeneous databases.

PubMed

Eronen, Lauri; Toivonen, Hannu

2012-06-06

Biological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases. Biomine is a system that integrates cross-references from several biological databases into a graph model with multiple types of edges, such as protein interactions, gene-disease associations and gene ontology annotations. Edges are weighted based on their type, reliability, and informativeness. We present Biomine and evaluate its performance in link prediction, where the goal is to predict pairs of nodes that will be connected in the future, based on current data. In particular, we formulate protein interaction prediction and disease gene prioritization tasks as instances of link prediction. The predictions are based on a proximity measure computed on the integrated graph. We consider and experiment with several such measures, and perform a parameter optimization procedure where different edge types are weighted to optimize link prediction accuracy. We also propose a novel method for disease-gene prioritization, defined as finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate Biomine by predicting future annotations in the source databases and prioritizing lists of putative disease genes. The experimental results show that Biomine has strong potential for predicting links when a set of selected candidate links is available. The predictions obtained using the entire Biomine dataset are shown to clearly outperform ones obtained using any single source of data alone, when different types of links are suitably weighted. In the gene prioritization task, an established reference set of disease-associated genes is useful, but the results show that under favorable conditions, Biomine can also perform well when no such information is

Clarifying the links between social support and health: culture, stress, and neuroticism matter.

PubMed

Park, Jiyoung; Kitayama, Shinobu; Karasawa, Mayumi; Curhan, Katherine; Markus, Hazel R; Kawakami, Norito; Miyamoto, Yuri; Love, Gayle D; Coe, Christopher L; Ryff, Carol D

2013-02-01

Although it is commonly assumed that social support positively predicts health, the empirical evidence has been inconsistent. We argue that three moderating factors must be considered: (1) support-approving norms (cultural context); (2) support-requiring situations (stressful events); and (3) support-accepting personal style (low neuroticism). Our large-scale cross-cultural survey of Japanese and US adults found significant associations between perceived support and health. The association was more strongly evident among Japanese (from a support-approving cultural context) who reported high life stress (in a support-requiring situation). Moreover, the link between support and health was especially pronounced if these Japanese were low in neuroticism.

Clarifying the links between social support and health: Culture, stress, and neuroticism matter

PubMed Central

Park, Jiyoung; Kitayama, Shinobu; Karasawa, Mayumi; Curhan, Katherine; Markus, Hazel R; Kawakami, Norito; Miyamoto, Yuri; Love, Gayle D; Coe, Christopher L; Ryff, Carol D

2012-01-01

Although it is commonly assumed that social support positively predicts health, the empirical evidence has been inconsistent. We argue that three moderating factors must be considered: (1) support-approving norms (cultural context); (2) support-requiring situations (stressful events); and (3) support-accepting personal style (low neuroticism). Our large-scale cross-cultural survey of Japanese and US adults found significant associations between perceived support and health. The association was more strongly evident among Japanese (from a support-approving cultural context) who reported high life stress (in a support-requiring situation). Moreover, the link between support and health was especially pronounced if these Japanese were low in neuroticism. PMID:22419414

Social Media, Open Science, and Data Science Are Inextricably Linked.

PubMed

Voytek, Bradley

2017-12-20

Should scientists use social media? Why practice open science? What is data science? Ten years ago, these phrases hardly existed. Now they are ubiquitous. Here I argue that these phenomena are inextricably linked and reflect similar underlying social and technological transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

Links Between Contexts and Middle to Late Childhood Social-Emotional Development.

PubMed

Duong, Jeffrey; Bradshaw, Catherine P

2017-12-01

Guided by the social-emotional learning (SEL) framework, we studied developmental trajectory patterns of five key competency outcomes spanning middle through late childhood: altruism, empathy, self-efficacy, aggression, and hyperactivity. We then assessed their links to middle childhood home, parental, and community contexts. Data from the Institute of Education Sciences' Social and Character Development Program, which comprised nearly 2,400 elementary school students who were followed from Grades 3 through 5, were analyzed using growth mixture modeling. Three trajectory groups emerged for each outcome, which were linked to childhood contexts. Positive parenting was associated with a lower likelihood of following a negative empathy trajectory among children. Neighborhood intergenerational closure promoted a stable self-efficacy trajectory. Residing in a high-risk community was linked to increasing normative beliefs about aggression. These findings suggest an important role of contexts in influencing childhood social-emotional development in the later elementary school years. © Society for Community Research and Action 2017.

Preschoolers Use Social Allegiances to Predict Behavior

ERIC Educational Resources Information Center

Chalik, Lisa; Rhodes, Marjorie

2014-01-01

Developing mechanisms for predicting human action is a critical task of early conceptual development. Three studies examined whether 4-year-old children (N = 149) use social allegiances to predict behavior, by testing whether they expect the experiences of social partners to influence individual action. After being exposed to a conflict between…

From the mouths of social media users: A focus group study exploring the social casino gaming-online gambling link.

PubMed

Kim, Hyoun S; Wohl, Michael J A; Gupta, Rina; Derevensky, Jeffrey

2016-03-01

Background and aims The potential link between social casino gaming and online gambling has raised considerable concerns among clinicians, researchers and policy makers. Unfortunately, however, there is a paucity of research examining this potential link, especially among young adults. This represents a significant gap given young adults are frequently exposed to and are players of social casino games. Methods To better understand the potential link between social casino games and online gambling, we conducted three focus groups (N = 30) at two large Canadian Universities with college students who were avid social media users (who are regularly exposed to social casino games). Results Many participants spontaneously mentioned that social casino games were a great opportunity to build gambling skills before playing for real money. Importantly, some participants expressed a belief that there is a direct progression from social casino gaming to online gambling. Conversely, others believed the transition to online gambling depended on a person's personality, rather than mere exposure to social casino games. While many young adults in our focus groups felt immune to the effects of social casino games, there was a general consensus that social casino games may facilitate the transition to online gambling among younger teenagers (i.e., 12-14 yr olds), due to the ease of accessibility and early exposure. Discussion The results of the present research point to the need for more study on the effects of social casino gambling as well as a discussion concerning regulation of social casino games in order to minimize their potential risks.

From the mouths of social media users: A focus group study exploring the social casino gaming–online gambling link

PubMed Central

Kim, Hyoun S.; Wohl, Michael J. A.; Gupta, Rina; Derevensky, Jeffrey

2016-01-01

Background and aims The potential link between social casino gaming and online gambling has raised considerable concerns among clinicians, researchers and policy makers. Unfortunately, however, there is a paucity of research examining this potential link, especially among young adults. This represents a significant gap given young adults are frequently exposed to and are players of social casino games. Methods To better understand the potential link between social casino games and online gambling, we conducted three focus groups (N = 30) at two large Canadian Universities with college students who were avid social media users (who are regularly exposed to social casino games). Results Many participants spontaneously mentioned that social casino games were a great opportunity to build gambling skills before playing for real money. Importantly, some participants expressed a belief that there is a direct progression from social casino gaming to online gambling. Conversely, others believed the transition to online gambling depended on a person’s personality, rather than mere exposure to social casino games. While many young adults in our focus groups felt immune to the effects of social casino games, there was a general consensus that social casino games may facilitate the transition to online gambling among younger teenagers (i.e., 12–14 yr olds), due to the ease of accessibility and early exposure. Discussion The results of the present research point to the need for more study on the effects of social casino gambling as well as a discussion concerning regulation of social casino games in order to minimize their potential risks. PMID:28092197

Attention Biases to Threat Link Behavioral Inhibition to Social Withdrawal over Time in Very Young Children

PubMed Central

Reeb-Sutherland, Bethany C.; McDermott, Jennifer Martin; White, Lauren K.; Henderson, Heather A.; Degnan, Kathryn A.; Hane, Amie A.; Pine, Daniel S.; Fox, Nathan A.

2013-01-01

Behaviorally inhibited children display a temperamental profile characterized by social withdrawal and anxious behaviors. Previous research, focused largely on adolescents, suggests that attention biases to threat may sustain high levels of behavioral inhibition (BI) over time, helping link early temperament to social outcomes. However, no prior studies examine the association between attention bias and BI before adolescence. The current study examined the interrelations among BI, attention biases to threat, and social withdrawal already manifest in early childhood. Children (N=187, 83 Male, Mage=61.96 months) were characterized for BI in toddlerhood (24 & 36 months). At 5 years, they completed an attention bias task and concurrent social withdrawal was measured. As expected, BI in toddlerhood predicted high levels of social withdrawal in early childhood. However, this relation was moderated by attention bias. The BI-withdrawal association was only evident for children who displayed an attention bias toward threat. The data provide further support for models associating attention with socioemotional development and the later emergence of clinical anxiety. PMID:21318555

Attention biases to threat link behavioral inhibition to social withdrawal over time in very young children.

PubMed

Pérez-Edgar, Koraly; Reeb-Sutherland, Bethany C; McDermott, Jennifer Martin; White, Lauren K; Henderson, Heather A; Degnan, Kathryn A; Hane, Amie A; Pine, Daniel S; Fox, Nathan A

2011-08-01

Behaviorally inhibited children display a temperamental profile characterized by social withdrawal and anxious behaviors. Previous research, focused largely on adolescents, suggests that attention biases to threat may sustain high levels of behavioral inhibition (BI) over time, helping link early temperament to social outcomes. However, no prior studies examine the association between attention bias and BI before adolescence. The current study examined the interrelations among BI, attention biases to threat, and social withdrawal already manifest in early childhood. Children (N=187, 83 Male, M (age)=61.96 months) were characterized for BI in toddlerhood (24 & 36 months). At 5 years, they completed an attention bias task and concurrent social withdrawal was measured. As expected, BI in toddlerhood predicted high levels of social withdrawal in early childhood. However, this relation was moderated by attention bias. The BI-withdrawal association was only evident for children who displayed an attention bias toward threat. The data provide further support for models associating attention with socioemotional development and the later emergence of clinical anxiety.

Disrupted prediction errors index social deficits in autism spectrum disorder

PubMed Central

Balsters, Joshua H; Apps, Matthew A J; Bolis, Dimitris; Lehner, Rea; Gallagher, Louise; Wenderoth, Nicole

2017-01-01

Abstract Social deficits are a core symptom of autism spectrum disorder; however, the perturbed neural mechanisms underpinning these deficits remain unclear. It has been suggested that social prediction errors—coding discrepancies between the predicted and actual outcome of another’s decisions—might play a crucial role in processing social information. While the gyral surface of the anterior cingulate cortex signalled social prediction errors in typically developing individuals, this crucial social signal was altered in individuals with autism spectrum disorder. Importantly, the degree to which social prediction error signalling was aberrant correlated with diagnostic measures of social deficits. Effective connectivity analyses further revealed that, in typically developing individuals but not in autism spectrum disorder, the magnitude of social prediction errors was driven by input from the ventromedial prefrontal cortex. These data provide a novel insight into the neural substrates underlying autism spectrum disorder social symptom severity, and further research into the gyral surface of the anterior cingulate cortex and ventromedial prefrontal cortex could provide more targeted therapies to help ameliorate social deficits in autism spectrum disorder. PMID:28031223

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

Introduction: Links between Social Interaction and Executive Function

ERIC Educational Resources Information Center

Lewis, Charlie; Carpendale, Jeremy I. M.

2009-01-01

The term executive function is used increasingly within developmental psychology and is often taken to refer to unfolding brain processes. We trace the origins of research on executive function to show that the link with social interaction has a long history. We suggest that a recent frenzy of research exploring methods for studying individual…

Depression and Social Anxiety in Children: Differential Links with Coping Strategies

ERIC Educational Resources Information Center

Wright, Mark; Banerjee, Robin; Hoek, Willemijn; Rieffe, Carolien; Novin, Sheida

2010-01-01

Strategies that children use for coping with stressors are known to be related to emotional adjustment, but not enough is understood about specific links with social anxiety and depression. The present investigation tested differentiated associations of social anxiety and depression with specific types of coping strategies, and evaluated the…

Macaques can predict social outcomes from facial expressions.

PubMed

Waller, Bridget M; Whitehouse, Jamie; Micheletta, Jérôme

2016-09-01

There is widespread acceptance that facial expressions are useful in social interactions, but empirical demonstration of their adaptive function has remained elusive. Here, we investigated whether macaques can use the facial expressions of others to predict the future outcomes of social interaction. Crested macaques (Macaca nigra) were shown an approach between two unknown individuals on a touchscreen and were required to choose between one of two potential social outcomes. The facial expressions of the actors were manipulated in the last frame of the video. One subject reached the experimental stage and accurately predicted different social outcomes depending on which facial expressions the actors displayed. The bared-teeth display (homologue of the human smile) was most strongly associated with predicted friendly outcomes. Contrary to our predictions, screams and threat faces were not associated more with conflict outcomes. Overall, therefore, the presence of any facial expression (compared to neutral) caused the subject to choose friendly outcomes more than negative outcomes. Facial expression in general, therefore, indicated a reduced likelihood of social conflict. The findings dispute traditional theories that view expressions only as indicators of present emotion and instead suggest that expressions form part of complex social interactions where individuals think beyond the present.

The separate and interactive effects of drinking motives and social anxiety symptoms in predicting drinking outcomes.

PubMed

Clerkin, Elise M; Barnett, Nancy

2012-05-01

Our goal was to test the separate and interactive effects of drinking motives and social anxiety symptoms in predicting drinking-related consumption and problems. Participants (N=730; 59.7% female) were undergraduate college students who completed measures of social anxiety symptoms, drinking motives, alcohol consumption, and drinking problems. Greater social anxiety symptoms were significantly associated with less alcohol consumption, and there was some evidence that greater social anxiety symptoms were also associated with greater alcohol-relevant problems. Significant interactions between social anxiety and motives indicated that a) alcohol use was most pronounced for individuals high in enhancement motives and low in social anxiety symptoms; and b) among participants low in coping motives, drinking problems were greater for individuals high (vs. low) in social anxiety symptoms. More fully identifying the individual difference factors that link social anxiety symptoms with drinking outcomes is important for informing prevention and intervention approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Separate and Interactive Effects of Drinking Motives and Social Anxiety Symptoms in Predicting Drinking Outcomes

PubMed Central

Clerkin, Elise M.; Barnett, Nancy

2012-01-01

PURPOSE Our goal was to test the separate and interactive effects of drinking motives and social anxiety symptoms in predicting drinking-related consumption and problems. METHODS Participants (N=730; 59.7% Female) were undergraduate college students who completed measures of social anxiety symptoms, drinking motives, alcohol consumption, and drinking problems. RESULTS Greater social anxiety symptoms were significantly associated with less alcohol consumption, and there was some evidence that greater social anxiety symptoms were also associated with greater alcohol-relevant problems. Significant interactions between social anxiety and motives indicated that a) alcohol use was most pronounced for individuals high in enhancement motives and low in social anxiety symptoms; and b) among participants low in coping motives, drinking problems were greater for individuals high (vs. low) in social anxiety symptoms. CONCLUSIONS More fully identifying the individual difference factors that link social anxiety symptoms with drinking outcomes is important for informing prevention and intervention approaches. PMID:22365887

Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis).

PubMed

VanderWaal, Kimberly L; Atwill, Edward R; Isbell, Lynne A; McCowan, Brenda

2014-03-01

Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in

Cognitive Biases and the Link between Shyness and Social Anxiety in Early Adolescence

ERIC Educational Resources Information Center

Weeks, Murray; Ooi, Laura L.; Coplan, Robert J.

2016-01-01

Shy children display wariness in unfamiliar social situations and often experience feelings of social anxiety. This study explored the potential mediating role of cognitive biases in the link between shyness and social anxiety in early adolescence. In particular, we focused on judgments of the probability and cost of negative social situations…

Predicting Positive and Negative Relationships in Large Social Networks.

PubMed

Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

2015-01-01

In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

Brain Structure Links Loneliness to Social Perception

PubMed Central

Kanai, Ryota; Bahrami, Bahador; Duchaine, Brad; Janik, Agnieszka; Banissy, Michael J.; Rees, Geraint

2012-01-01

Summary Loneliness is the distressing feeling associated with the perceived absence of satisfying social relationships [1]. Loneliness is increasingly prevalent in modern societies [2, 3] and has detrimental effects on health and happiness [4, 5]. Although situational threats to social relationships can transiently induce the emotion of loneliness, susceptibility to loneliness is a stable trait that varies across individuals [6–8] and is to some extent heritable [9–11]. However, little is known about the neural processes associated with loneliness (but see [12–14]). Here, we hypothesized that individual differences in loneliness might be reflected in the structure of the brain regions associated with social processes [15]. To test this hypothesis, we used voxel-based morphometry and showed that lonely individuals have less gray matter in the left posterior superior temporal sulcus (pSTS)—an area implicated in basic social perception. As this finding predicted, we further confirmed that loneliness was associated with difficulty in processing social cues. Although other sociopsychological factors such as social network size, anxiety, and empathy independently contributed to loneliness, only basic social perception skills mediated the association between the pSTS volume and loneliness. Taken together, our results suggest that basic social perceptual abilities play an important role in shaping an individual’s loneliness. PMID:23041193

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of

Are emotion and mind understanding differently linked to young children's social adjustment? Relationships between behavioral consequences of emotions, false belief, and SCBE.

PubMed

Deneault, Joane; Ricard, Marcelle

2013-01-01

According to empirical findings, emotional knowledge and false belief understanding seem to be differently linked to social adjustment. However, whereas false belief is assessed through the capacity to identify its behavioral consequences, emotion tasks usually rely on the comprehension of facial expressions and of the situational causes of emotions. The authors examined if the documented relationship between social adjustment and emotion knowledge in children extends to the understanding of behavioral consequences of emotions. Eighty French-speaking preschoolers undertook false belief and consequence-of-emotion tasks. Their social adjustment was measured by the Social Competence and Behavior Evaluation. Children's language ability, their parent's level of education, and the familial socioeconomic score were taken into account. Results showed that children's social adjustment was significantly predicted by their knowledge of emotion, but not by their understanding of false belief. The findings confirm the special status of emotion among mental states for social adaptation and specify which dimensions of adaptation to peers and adults are predicted by the child's emotion understanding. They also suggest that the distinction between mind and emotion understanding may be conceptual rather than methodological.

Gene-environment interplay in the link of friends' and nonfriends' behaviors with children's social reticence in a competitive situation.

PubMed

Guimond, Fanny-Alexandra; Brendgen, Mara; Vitaro, Frank; Forget-Dubois, Nadine; Dionne, Ginette; Tremblay, Richard E; Boivin, Michel

2014-03-01

This study used a genetically informed design to assess the effects of friends' and nonfriends' reticent and dominant behaviors on children's observed social reticence in a competitive situation. Potential gene-environment correlations (rGE) and gene-environment interactions (GxE) in the link between (a) friends' and nonfriends' behaviors and (b) children's social reticence were examined. The sample comprised 466 twin children (i.e., the target children), each of whom was assessed in kindergarten together with a same-sex friend and two nonfriend classmates of either sex. Multilevel regression analyses revealed that children with a genetic disposition for social reticence showed more reticent behavior in the competitive situation and were more likely to affiliate with reticent friends (i.e., rGE). Moreover, a higher level of children's reticent behavior was predicted by their friends' higher social reticence (particularly for girls) and their friends' higher social dominance, independently of children's genetic disposition. Children's social reticence was also predicted by their nonfriends' behaviors. Specifically, children were less reticent when male nonfriends showed high levels of social reticence in the competitive situation, and this was particularly true for children with a genetic disposition for social reticence (i.e., GxE). Moreover, children genetically vulnerable for social reticence seemed to foster dominant behavior in their female nonfriend peers (i.e., rGE). In turn, male nonfriends seemed to be more dominant as soon as the target children were reticent, even if the target children did not have a stable genetic disposition for this behavior. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Aberrant link between empathy and social attribution style in borderline personality disorder.

PubMed

Homan, Philipp; Reddan, Marianne C; Brosch, Tobias; Koenigsberg, Harold W; Schiller, Daniela

2017-11-01

In social interactions, we often need to quickly infer why other people do what they do. More often than not, we infer that behavior is a result of personality rather than circumstances. It is unclear how the tendency itself may contribute to psychopathology and interpersonal dysfunction. Borderline personality disorder (BPD) is characterized by severe interpersonal dysfunction. Here, we investigated if this dysfunction is related to the tendency to over-attribute behaviors to personality traits. Healthy controls and patients with BPD judged positive and negative behaviors presented within a situational constraint during functional magnetic resonance imaging. Before the experiment, we measured trait levels of empathy, paranoia, and need for cognition. Behaviorally, we found that empathy levels predicted the tendency to attribute behavior to traits in healthy controls, whereas in patients with BPD this relationship was significantly weakened. Whole brain analysis of group-by-empathy interaction revealed that when participants judged the behavior during the attribution phase, several brain regions implicated in mentalizing distinguished patients from controls: In healthy controls, neural activity scaled negatively with empathy, but this relationship was reversed in BPD patients. Due to the cross-sectional study design we cannot establish a causal link between empathy and social attributions. These findings indicate that the self-reported tendency to feel for others is related to the tendency to integrate situational information beyond personality. In BPD patients, by contrast, the association between empathy and attribution was significantly weaker, rendering empathy less informative in predicting the overall attribution style. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting externalizing and internalizing behavior in kindergarten: examining the buffering role of early social support.

PubMed

Heberle, Amy E; Krill, Sarah C; Briggs-Gowan, Margaret J; Carter, Alice S

2015-01-01

This study tested an ecological model predicting children's behavior problems in kindergarten from risk and protective factors (parent psychological distress, parenting behavior, and social support) during early childhood. Study participants were 1,161 sociodemographically diverse mother-child pairs that participated in a longitudinal birth cohort study. The predictor variables were collected at two separate time points and based on parent reports; children were an average of 2 years old at Time 1 and 3 years old at Time 2. The outcome measures were collected when children reached kindergarten and were 6 years old on average. Our results show that early maternal psychological distress, mediated by suboptimal parenting behavior, predicts children's externalizing and internalizing behaviors in kindergarten. Moreover, early social support buffers the relations between psychological distress and later suboptimal parenting behavior and between suboptimal parenting behavior and later depressive/withdrawn behavior. Our findings have several implications for early intervention and prevention efforts. Of note, informal social support appears to play an important protective role in the development of externalizing and internalizing behavior problems, weakening the link between psychological distress and less optimal parenting behavior and between suboptimal parenting behavior and children's withdrawal/depression symptoms. Increasing social support may be a productive goal for family and community-level intervention.

Prospective Links between Social Anxiety and Adolescent Peer Relations

ERIC Educational Resources Information Center

Tillfors, Maria; Persson, Stefan; Willen, Maria; Burk, William J.

2012-01-01

This study examines bi-directional links between social anxiety and multiple aspects of peer relations (peer acceptance, peer victimization, and relationship quality) in a longitudinal sample of 1528 adolescents assessed twice with one year between (754 females and 774 males; M = 14.7 years of age). Lower levels of peer acceptance predicted…

Genetic variants linked to education predict longevity

PubMed Central

Marioni, Riccardo E.; Ritchie, Stuart J.; Joshi, Peter K.; Hagenaars, Saskia P.; Fischer, Krista; Adams, Mark J.; Hill, W. David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C.; Wilson, James F.; Hayward, Caroline; Esko, Tõnu; Porteous, David J.; Gale, Catharine R.; Deary, Ian J.

2016-01-01

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members’ polygenic profile score for education to predict their parents’ longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total ndeaths = 79,702) and ∼2.4% lower risk for fathers (total ndeaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity. PMID:27799538

Genetic variants linked to education predict longevity.

PubMed

Marioni, Riccardo E; Ritchie, Stuart J; Joshi, Peter K; Hagenaars, Saskia P; Okbay, Aysu; Fischer, Krista; Adams, Mark J; Hill, W David; Davies, Gail; Nagy, Reka; Amador, Carmen; Läll, Kristi; Metspalu, Andres; Liewald, David C; Campbell, Archie; Wilson, James F; Hayward, Caroline; Esko, Tõnu; Porteous, David J; Gale, Catharine R; Deary, Ian J

2016-11-22

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total n deaths = 79,702) and ∼2.4% lower risk for fathers (total n deaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity.

The degree-related clustering coefficient and its application to link prediction

NASA Astrophysics Data System (ADS)

Liu, Yangyang; Zhao, Chengli; Wang, Xiaojie; Huang, Qiangjuan; Zhang, Xue; Yi, Dongyun

2016-07-01

Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

Prospective links between ethnic socialization, ethnic and American identity, and well-being among Asian-American adolescents.

PubMed

Gartner, Meaghan; Kiang, Lisa; Supple, Andrew

2014-10-01

Ethnic socialization and ethnic identity have been related to positive outcomes, but little research has examined these associations longitudinally. This three-wave study prospectively linked socialization messages at Time 1, ethnic identity and American identity at Time 2, and self-esteem and depressive symptoms at Time 3 in 147 (58% female; 25% first-generation) Asian-American adolescents. The results indicated positive links between cultural socialization messages and ethnic and American identity, though the latter association was significant only for females. Ethnic identity was positively related to self-esteem, and mediated the positive effect of cultural socialization on self-esteem. The promotion of mistrust was positively linked to self-esteem and negatively related to ethnic identity, though this latter association was significant for foreign-born youth only. Our findings highlight the importance of elucidating prospective links in identity development, and examining gender and generational differences within them.

Linking Language Assessments: An Example in a Low Stakes Context.

ERIC Educational Resources Information Center

North, Brian

2000-01-01

Linking language assessments is a matter of greater concern with the advent of educational frameworks used to orient curricula and profile attainment. Outlines practical ways the principles of techniques recognized for linking separate assessments--equating, calibrating, statistical moderation, predicting (or benchmarking), and social moderation…

The "weakest link" as an indicator of cognitive vulnerability differentially predicts symptom dimensions of anxiety in adolescents in China.

PubMed

Wang, Junyi; Wang, Danyang; Cui, Lixia; McWhinnie, Chad M; Wang, Li; Xiao, Jing

2017-08-01

This multiwave longitudinal study examined the cognitive vulnerability-stress component of hopelessness theory to differentially predict symptom dimensions of anxiety using a "weakest link" approach in a sample of adolescents from Hunan Province, China. Baseline and 6-month follow-up data were obtained from 553 middle-school students. During an initial assessment, participants completed measures of assessing their weakest links, anxious symptoms, and the occurrence of stress. Participants subsequently completed measures assessing stress, and anxious symptoms one a month for six months. Higher weakest link scores were associated with greater increases in the harm avoidance and separation anxiety/panic dimensions, but not the physical or social anxiety dimension, of anxious symptoms following stress in Chinese adolescents. These results support the applicability of the "weakest link" approach, derived from hopelessness theory, in Chinese adolescents. Weakest link scores as cognitive vulnerability factors may play a role in the development of anxious symptoms, especially in the cognitive dimensions (e.g., harm avoidance and separation anxiety/panic). Our findings also have potential value in explaining the effectiveness of cognitive relevant therapy in treating the cognitive dimensions of anxious symptoms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linking Individual and Collective Behavior in Adaptive Social Networks

NASA Astrophysics Data System (ADS)

Pinheiro, Flávio L.; Santos, Francisco C.; Pacheco, Jorge M.

2016-03-01

Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N -person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Rescripting Early Memories Linked to Negative Images in Social Phobia: A Pilot Study

ERIC Educational Resources Information Center

Wild, Jennifer; Hackmann, Ann; Clark, David M.

2008-01-01

Negative self-images are a maintaining factor in social phobia. A retrospective study (Hackmann, A., Clark, D.M., McManus, F. (2000). Recurrent images and early memories in social phobia. Behaviour Research and Therapy, 38, 601-610) suggested that the images may be linked to early memories of unpleasant social experiences. This preliminary study…

Accuracy test for link prediction in terms of similarity index: The case of WS and BA models

NASA Astrophysics Data System (ADS)

Ahn, Min-Woo; Jung, Woo-Sung

2015-07-01

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barabási-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data.

PubMed

Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J; Kim, Doh Kwan

2018-04-01

Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events.

What measure of interpersonal dependency predicts changes in social support?

PubMed

Shahar, Golan

2008-01-01

One of the most intriguing characteristics of interpersonal dependency is its ability to predict elevated levels of social support. Yet studies of interpersonal dependency use various measures to assess this effect. In this study, I compared 3 commonly used measures of interpersonal dependency in terms of their prediction of social support: Hirschfield's Interpersonal Dependency Inventory (IDI; Hirschfeld et al., 1977), the dependency factor of the Depressive Experiences Questionnaire (DEQ; Blatt, D'Afflitti, & Quinlan, 1976), and the Dependency subscale of the Personal Style Inventory (PSI; Robins et al., 1994). A total of 152 undergraduates were administered these measures as well as measures of depressive symptoms and social support a week prior to their first exam period and a week after this period (interval time = 8 weeks). DEQ-dependency predicted an increase in social support, whereas PSI-Dependency and IDI predicted a decrease in social support over time. DEQ-dependency appears to capture better than the other 2 measures the dialectic tension between risk and resilience in interpersonal dependency.

Daily Social Interactions and the Biological Stress Response: Are There Age Differences in Links Between Social Interactions and Alpha-Amylase?

PubMed

Birditt, Kira S; Tighe, Lauren A; Nevitt, Michael R; Zarit, Steven H

2017-12-12

According to the strength and vulnerability integration (SAVI) model, older people are better able to avoid negative social interactions than younger people, but when they do experience negative interactions, they are equally or more emotionally and physiologically reactive than younger people. Less is known about the links between daily negative and positive social encounters and the sympathetic adrenal medullary system (a key stress pathway) and whether there are age differences in these links. This study considers whether negative and positive social interactions are associated with diurnal alpha-amylase (a measure of the sympathetic adrenal medullary system) and whether there are differences in these links by age. Participants were from the Daily Health, Stress, and Relationship Study, which includes a random sample of 89 individuals (aged 40-95) who completed 14 days of daily diary interviews and provided saliva samples four times a day (wake, 30 min after wake, lunch, and bedtime) for four of those days that were assayed for alpha-amylase. Days in which people reported more negative interactions were associated with flatter morning declines in alpha-amylase, indicating greater stress. Links between positive interactions and diurnal alpha-amylase varied by age group. Findings are consistent with the SAVI model indicating that older adults respond differently to social stimuli than younger people. © The Author(s) 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Predicting Social Trust with Binary Logistic Regression

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph; Hufstedler, Shirley

2015-01-01

This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

PubMed

Crawford, Jarret T; Brandt, Mark J; Inbar, Yoel; Chambers, John R; Motyl, Matt

2017-03-01

Liberals and conservatives both express prejudice toward ideologically dissimilar others (Brandt et al., 2014). Previous work on ideological prejudice did not take advantage of evidence showing that ideology is multidimensional, with social and economic ideologies representing related but separable belief systems. In 5 studies (total N = 4912), we test 3 competing hypotheses of a multidimensional account of ideological prejudice. The dimension-specific symmetry hypothesis predicts that social and economic ideologies differentially predict prejudice against targets who are perceived to vary on the social and economic political dimensions, respectively. The social primacy hypothesis predicts that such ideological worldview conflict is experienced more strongly along the social than economic dimension. The social-specific asymmetry hypothesis predicts that social conservatives will be more prejudiced than social liberals, with no specific hypotheses for the economic dimension. Using multiple target groups, multiple prejudice measures (e.g., global evaluations, behavior), and multiple social and economic ideology measures (self-placement, issue positions), we found relatively consistent support for the dimension-specific symmetry and social primacy hypotheses, and no support for the social-specific asymmetry hypothesis. These results suggest that worldview conflict and negative intergroup attitudes and behaviors are dimension-specific, but that the social dimension appears to inspire more political conflict than the economic dimension. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data

PubMed Central

Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J.; Kim, Doh Kwan

2018-01-01

Objective Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. Methods The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Results Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. Conclusion These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events. PMID:29614852

Social group dynamics predict stress variability among children in a New Zealand classroom.

PubMed

Spray, Julie; Floyd, Bruce; Littleton, Judith; Trnka, Susanna; Mattison, Siobhan

2018-03-27

Previous research proposes stress as a mechanism for linking social environments and biological bodies. In particular, non-human primate studies investigate relationships between cortisol as a measure of stress response and social hierarchies. Because human social structures often include hierarchies of dominance and social status, humans may exhibit similar patterns. Studies of non-human primates, however, have not reached consistent conclusions with respect to relationships between social position and levels of cortisol. While human studies report associations between cortisol and various aspects of social environments, studies that consider social status as a predictor of stress response also report mixed results. Others have argued that perceptions of social status may have different implications for stress response depending upon social context. We propose here that characteristics of children's social networks may be a better predictor of central tendencies and variability of stress response than their perceptions of social status. This is evaluated among 24 children from 9.4 to 11.3 years of age in one upper middle-class New Zealand primary school classroom, assessed through observation within the classroom, self-reports during semi-structured interviews and 221 serial saliva samples provided daily over 10 consecutive school days. A synthetic assessment of the children's networks and peer-relationships was developed prior to saliva-cortisol analysis. We found that greater stability of peer-relationships within groups significantly predicts lower within-group variation in mid-morning cortisol over the two-week period, but not overall within-group differences in mean cortisol. Copyright © 2018 Elsevier GmbH. All rights reserved.

Predicting Externalizing and Internalizing Behavior in Kindergarten: Examining the Buffering Role of Early Social Support

PubMed Central

Heberle, Amy E.; Krill, Sarah C.; Briggs-Gowan, Margaret J.; Carter, Alice S.

2014-01-01

Objective This study tested an ecological model predicting children’s behavior problems in kindergarten from risk and protective factors (parent psychological distress, parenting behavior, and social support) during early childhood. Method Study participants were 1161 socio-demographically diverse mother-child pairs who participated in a longitudinal birth cohort study. The predictor variables were collected at two separate time points and based on parent reports; children were an average of two years old at Time 1 and three years old at Time 2. The outcome measures were collected when children reached Kindergarten and were six years old on average. Results Our results show that early maternal psychological distress, mediated by sub-optimal parenting behavior, predicts children’s externalizing and internalizing behaviors in kindergarten. Moreover, early social support buffers the relations between psychological distress and later sub-optimal parenting behaviors and between sub-optimal parenting behavior and later depressive/withdrawn behavior. Conclusions Our findings have several implications for early intervention and prevention efforts. Of note, informal social support appears to play an important protective role in the development of externalizing and internalizing behavior problems, weakening the link between psychological distress and less optimal parenting behavior and between sub-optimal parenting behavior and children’s withdrawal/depression symptoms. Increasing social support may be a productive goal for family and community-level intervention. PMID:24697587

Social Factors That Predict Fear of Academic Success

ERIC Educational Resources Information Center

Gore, Jonathan S.; Thomas, Jessica; Jones, Stevy; Mahoney, Lauren; Dukes, Kristina; Treadway, Jodi

2016-01-01

Fear of academic success is ultimately a fear of social exclusion. Therefore, various forms of social inclusion may alleviate this fear. Three studies tested the hypothesis that social inclusion variables negatively predict fear of success. In Study 1, middle and high school students (n = 129) completed surveys of parental involvement, parental…

Predicting national suicide numbers with social media data.

PubMed

Won, Hong-Hee; Myung, Woojae; Song, Gil-Young; Lee, Won-Hee; Kim, Jong-Won; Carroll, Bernard J; Kim, Doh Kwan

2013-01-01

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors - consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

Predicting National Suicide Numbers with Social Media Data

PubMed Central

Won, Hong-Hee; Song, Gil-Young; Lee, Won-Hee; Kim, Jong-Won; Carroll, Bernard J.

2013-01-01

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention. PMID:23630615

Predicting anxious response to a social challenge: the predictive utility of the social interaction anxiety scale and the social phobia scale in a college population.

PubMed

Gore, K L; Carter, M M; Parker, S

2002-06-01

Trait anxiety is believed to be a hierarchical construct composed of several lower-order factors (Adv. Behav. Res. Therapy, 15 (1993) 147; J. Anxiety Disorders, 9 (1995) 163). Assessment devices such as the Social Interaction Anxiety Scale, the Social Phobia Scale (SIAS and SPS; Behav. Res. Therapy, 36 (4) (1998) 455), and the Anxiety Sensitivity Index (ASI; Behav. Res. Therapy, 24 (1986) 1) are good measures of the presumably separate lower-order factors. This study compared the effectiveness of the SIAS, SPS, ASI-physical scale and STAI-T (State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press (1970)) as predictors of anxious response to a social challenge (asking an aloof confederate out on a date). Consistent with the hierarchical model of anxiety, the measures of trait anxiety were moderately correlated with each other and each was a significant predictor of anxious response. The specific measures of trait social anxiety were slightly better predictors of anxious response to the social challenge than was either the ASI-physical scale or the STAI-T. The results provide evidence of the predictive validity of these social trait measures and some support for their specificity in the prediction of anxious response to a social challenge.

Marine reserves as linked social-ecological systems.

PubMed

Pollnac, Richard; Christie, Patrick; Cinner, Joshua E; Dalton, Tracey; Daw, Tim M; Forrester, Graham E; Graham, Nicholas A J; McClanahan, Timothy R

2010-10-26

Marine reserves are increasingly recognized as having linked social and ecological dynamics. This study investigates how the ecological performance of 56 marine reserves throughout the Philippines, Caribbean, and Western Indian Ocean (WIO) is related to both reserve design features and the socioeconomic characteristics in associated coastal communities. Ecological performance was measured as fish biomass in the reserve relative to nearby areas. Of the socioeconomic variables considered, human population density and compliance with reserve rules had the strongest effects on fish biomass, but the effects of these variables were region specific. Relationships between population density and the reserve effect on fish biomass were negative in the Caribbean, positive in the WIO, and not detectable in the Philippines. Differing associations between population density and reserve effectiveness defy simple explanation but may depend on human migration to effective reserves, depletion of fish stocks outside reserves, or other social factors that change with population density. Higher levels of compliance reported by resource users was related to higher fish biomass in reserves compared with outside, but this relationship was only statistically significant in the Caribbean. A heuristic model based on correlations between social, cultural, political, economic, and other contextual conditions in 127 marine reserves showed that high levels of compliance with reserve rules were related to complex social interactions rather than simply to enforcement of reserve rules. Comparative research of this type is important for uncovering the complexities surrounding human dimensions of marine reserves and improving reserve management.

Trait aggressiveness does not predict social dominance of rats in the Visible Burrow System.

PubMed

Buwalda, Bauke; Koolhaas, Jaap M; de Boer, Sietse F

2017-09-01

Hierarchical social status greatly influences health and well-being in mammals, including humans. The social rank of an individual is established during competitive encounters with conspecifics. Intuitively, therefore, social dominance and aggressiveness may seem intimately linked. Yet, whether an aggressive personality trait may predispose individuals to a particular rank in a social colony setting remains largely unclear. Here we tested the hypothesis that high trait aggressiveness in Wildtype Groningen (WTG) rats, as assessed in a classic resident-intruder offensive aggression paradigm predicts social dominance in a mixed-sex colony housing using the Visible Burrow System (VBS). We also hypothesized that hierarchical steepness, as reflected in the number and intensity of the social conflicts, positively correlates with the average level of trait aggressiveness of the male subjects in the VBS. Clear and stable hierarchical ranking was formed within a few days in VBS colonies as indicated and reflected by a rapid loss of body weight in subordinates which stabilized after 2-3days. Social conflicts, that occurred mainly during these first few days, also resulted in bite wounds in predominantly subordinate males. Data clearly showed that trait aggressiveness does not predict dominance status. The most aggressive male in a mixed sex group of conspecifics living in a closed VBS environment does not always become the dominant male. In addition, data did not convincingly indicate that in colonies with only highly aggressive males, agonistic interactions were more intense. Number of bite wounds and body weight loss did not positively correlate with trait-aggressiveness of subordinates. In this study, rats from this wild-derived rat strain behave differently from Long-Evans laboratory rats that have been studied up till now in many experiments using the VBS. Strain dependent differences in the capacity to display appropriate social behavior fitting an adaptive strategy to

Exploratory behavior is linked to stress physiology and social network centrality in free-living house finches (Haemorhous mexicanus).

PubMed

Moyers, Sahnzi C; Adelman, James S; Farine, Damien R; Moore, Ignacio T; Hawley, Dana M

2018-06-01

Animal personality has been linked to individual variation in both stress physiology and social behaviors, but few studies have simultaneously examined covariation between personality traits, stress hormone levels, and behaviors in free-living animals. We investigated relationships between exploratory behavior (one aspect of animal personality), stress physiology, and social and foraging behaviors in wild house finches (Haemorhous mexicanus). We conducted novel environment assays after collecting samples of baseline and stress-induced plasma corticosterone concentrations from a subset of house finches. We then fitted individuals with Passive Integrated Transponder tags and monitored feeder use and social interactions at radio-frequency identification equipped bird feeders. First, we found that individuals with higher baseline corticosterone concentrations exhibit more exploratory behaviors in a novel environment. Second, more exploratory individuals interacted with more unique conspecifics in the wild, though this result was stronger for female than for male house finches. Third, individuals that were quick to begin exploring interacted more frequently with conspecifics than slow-exploring individuals. Finally, exploratory behaviors were unrelated to foraging behaviors, including the amount of time spent on bird feeders, a behavior previously shown to be predictive of acquiring a bacterial disease that causes annual epidemics in house finches. Overall, our results indicate that individual differences in exploratory behavior are linked to variation in both stress physiology and social network traits in free-living house finches. Such covariation has important implications for house finch ecology, as both traits can contribute to fitness in the wild. Copyright © 2018 Elsevier Inc. All rights reserved.

The role of postdeployment social factors in linking deployment experiences and current posttraumatic stress disorder symptomatology among male and female veterans.

PubMed

Smith, Brian N; Wang, Joyce M; Vaughn-Coaxum, Rachel A; Di Leone, Brooke A L; Vogt, Dawne

2017-01-01

The postdeployment social context is likely highly salient in explaining mental health symptoms following deployment. The aim of this study was to examine the role of postdeployment social factors (social support and social reintegration difficulty) in linking deployment-related experiences (warfare exposure, sexual harassment, concerns about relationship disruptions, and deployment social support) and posttraumatic stress disorder (PTSD) symptomatology in male and female veterans. A survey was administered to 998 potential participants (after accounting for undeliverable mail) who had returned from deployment to Afghanistan or Iraq. Completed surveys were received from 469 veterans, yielding a response rate of 47%. Hypotheses were examined using structural equation modeling. For male and female veterans, deployment factors predicted later PTSD symptoms through postdeployment social support and social reintegration, with lower support and higher social reintegration difficulty both associated with higher PTSD symptomatology. While the final models for women and men indicated similar risk mechanisms, some differences in pathways were observed. Sexual harassment presented more of a risk for women, whereas lower social support was a greater risk factor for men. Postdeployment social factors appear to represent potentially important targets for interventions aiming to reduce the potential impact of stressful deployment experiences.

Web-Based Knowledge Exchange through Social Links in the Workplace

ERIC Educational Resources Information Center

Filipowski, Tomasz; Kazienko, Przemyslaw; Brodka, Piotr; Kajdanowicz, Tomasz

2012-01-01

Knowledge exchange between employees is an essential feature of recent commercial organisations on the competitive market. Based on the data gathered by various information technology (IT) systems, social links can be extracted and exploited in knowledge exchange systems of a new kind. Users of such a system ask their queries and the system…

Understanding the links between ecosystem health and social system well-being: an annotated bibliography.

Treesearch

Dawn M. Elmer; Harriet H. Christensen; Ellen M. Donoghue; [Compilers].

2002-01-01

This bibliography focuses on the links between social system well-being and ecosystem health. It is intended for public land managers and scientists and students of social and natural sciences. Multidisciplinary science that addresses the interconnections between the social system and the ecosystem is presented. Some of the themes and strategies presented are policy...

Does anxiety sensitivity predict symptoms of panic, depression, and social anxiety?

PubMed

Grant, DeMond M; Beck, J Gayle; Davila, Joanne

2007-09-01

This study examined whether the lower-order factors of the Anxiety Sensitivity Index (ASI) exhibited specificity in predicting symptoms of panic, depression, and social anxiety prospectively. This question was addressed using a sample of undergraduates stratified to represent low, medium, and high levels of anxiety sensitivity (AS). It was hypothesized that the physical concerns, mental concerns, and social concerns subscales of the ASI would predict increases in panic, depression, and social anxiety symptoms, respectively, one year later. Results found that the physical concerns subscale predicted increases in both panic and depressive symptoms. Neither the mental concerns nor the social concerns subscales predicted significant variance in any of the Time 2 symptoms. Theoretical implications of these data for AS are discussed.

Social Goals, Aggression, Peer Preference, and Popularity: Longitudinal Links during Middle School

ERIC Educational Resources Information Center

Ojanen, Tiina; Findley-Van Nostrand, Danielle

2014-01-01

Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic…

Learned social hopelessness: the role of explanatory style in predicting social support during adolescence.

PubMed

Ciarrochi, Joseph; Heaven, Patrick C L

2008-12-01

Almost no research has examined the impact of explanatory style on social adjustment. We hypothesised that adolescents with a pessimistic style would be less likely to develop and maintain social support networks. Seven hundred and nineteen students (351 males and 366 females; 2 unknown; M(AGE) = 12.28, SD = .49) completed an anonymous survey in Grades 7 through 10. Explanatory style was assessed in Grades 7 and 9, sadness was assessed in Grades 7 through 10, and quantity and quality of social support was assessed in Grades 8, 9, and 10. Structural equation modelling was used to conduct cross-lagged panel analyses of the four waves of data. Pessimistic explanatory style predicted lower levels of social support, and lower social support from the family predicted higher levels of pessimistic explanatory style. Additional analyses suggested that the effects could not be explained by sadness or by assuming that pessimistic adolescents where less liked by their peers. Pessimistic adolescents feel unable to influence their social worlds in positive ways and consequently may not take actions to develop and maintain social support networks.

Social in, social out: How the brain responds to social language with more social language.

PubMed

O'Donnell, Matthew Brook; Falk, Emily B; Lieberman, Matthew D

Social connection is a fundamental human need. As such, people's brains are sensitized to social cues, such as those carried by language, and to promoting social communication. The neural mechanisms of certain key building blocks in this process, such as receptivity to and reproduction of social language, however, are not known. We combined quantitative linguistic analysis and neuroimaging to connect neural activity in brain regions used to simulate the mental states of others with exposure to, and re-transmission of, social language. Our results link findings on successful idea transmission from communication science, sociolinguistics and cognitive neuroscience to prospectively predict the degree of social language that participants utilize when re-transmitting ideas as a function of 1) initial language inputs and 2) neural activity during idea exposure.

Exploring context and content links in social media: a latent space method.

PubMed

Qi, Guo-Jun; Aggarwal, Charu; Tian, Qi; Ji, Heng; Huang, Thomas S

2012-05-01

Social media networks contain both content and context-specific information. Most existing methods work with either of the two for the purpose of multimedia mining and retrieval. In reality, both content and context information are rich sources of information for mining, and the full power of mining and processing algorithms can be realized only with the use of a combination of the two. This paper proposes a new algorithm which mines both context and content links in social media networks to discover the underlying latent semantic space. This mapping of the multimedia objects into latent feature vectors enables the use of any off-the-shelf multimedia retrieval algorithms. Compared to the state-of-the-art latent methods in multimedia analysis, this algorithm effectively solves the problem of sparse context links by mining the geometric structure underlying the content links between multimedia objects. Specifically for multimedia annotation, we show that an effective algorithm can be developed to directly construct annotation models by simultaneously leveraging both context and content information based on latent structure between correlated semantic concepts. We conduct experiments on the Flickr data set, which contains user tags linked with images. We illustrate the advantages of our approach over the state-of-the-art multimedia retrieval techniques.

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

Factors Influencing the Link between Social Anxiety and Peer Acceptance: Contributions of Social Skills and Close Friendships during Middle Childhood

ERIC Educational Resources Information Center

Greco, Laurie A.; Morris, Tracy L.

2005-01-01

Childhood social anxiety consistently has been linked with low levels of peer acceptance, yet little is known about the factors contributing to this association. We therefore examined the mediating and moderating role of social skills and close friendships, two conceptually and empirically relevant variables which were hypothesized to contribute…

Community resilience and health: the role of bonding, bridging, and linking aspects of social capital.

PubMed

Poortinga, Wouter

2012-03-01

The current study draws on data from the 2007 and 2009 Citizenship Survey collected in England (n=17,572) to explore the role of social capital in building community resilience and health, using the bonding, bridging, and linking social capital framework of Szreter and Woolcock (2004). The results show that the indicators of the different types of social capital are only weakly interrelated, suggesting that they capture different aspects of the social environment. In line with the expectations, most indicators of bonding, bridging, and linking social capital were significantly associated with neighbourhood deprivation and self-reported health. In particular bonding and bridging social cohesion, civic participation, heterogeneous socio-economic relationships, and political efficacy and trust appeared important for community health after controlling for neighbourhood deprivation. However, no support was found for the hypothesis that the different aspects help buffer against the detrimental influences of neighbourhood deprivation. Copyright © 2011 Elsevier Ltd. All rights reserved.

OXTR polymorphism predicts social relationships through its effects on social temperament

PubMed Central

Wright, Aidan G. C.; Troxel, Wendy M.; Ferrell, Robert E.; Flory, Janine D.; Manuck, Stephen B.

2015-01-01

Humans have a fundamental need for strong interpersonal bonds, yet individuals differ appreciably in their degree of social integration. That these differences are also substantially heritable has spurred interest in biological mechanisms underlying the quality and quantity of individuals’ social relationships. We propose that polymorphic variation in the oxytocin receptor gene (OXTR) associates with complex social behaviors and social network composition through intermediate effects on negative affectivity and the psychological processing of socially relevant information. We tested a hypothesized social cascade from the molecular level (OXTR variation) to the social environment, through negative affectivity and inhibited sociality, in a sample of 1295 men and women of European American (N = 1081) and African American (N = 214) ancestry. Compared to European Americans having any T allele of rs1042778, individuals homozygous for the alternate G allele reported significantly lower levels of negative affectivity and inhibited sociality, which in turn predicted significantly higher levels of social support and a larger/more diverse social network. Moreover, the effect of rs1042778 variation on social support was fully accounted for by associated differences in negative affectivity and inhibited sociality. Results replicated in the African American sample. Findings suggest that OXTR variation modulates levels of social support via proximal impacts on individual temperament. PMID:25326040

Emotional Intelligence predicts individual differences in social exchange reasoning.

PubMed

Reis, Deidre L; Brackett, Marc A; Shamosh, Noah A; Kiehl, Kent A; Salovey, Peter; Gray, Jeremy R

2007-04-15

When assessed with performance measures, Emotional Intelligence (EI) correlates positively with the quality of social relationships. However, the bases of such correlations are not understood in terms of cognitive and neural information processing mechanisms. We investigated whether a performance measure of EI is related to reasoning about social situations (specifically social exchange reasoning) using versions of the Wason Card Selection Task. In an fMRI study (N=16), higher EI predicted hemodynamic responses during social reasoning in the left frontal polar and left anterior temporal brain regions, even when controlling for responses on a very closely matched task (precautionary reasoning). In a larger behavioral study (N=48), higher EI predicted faster social exchange reasoning, after controlling for precautionary reasoning. The results are the first to directly suggest that EI is mediated in part by mechanisms supporting social reasoning and validate a new approach to investigating EI in terms of more basic information processing mechanisms.

Global brain dynamics during social exclusion predict subsequent behavioral conformity

PubMed Central

Wasylyshyn, Nick; Hemenway Falk, Brett; Garcia, Javier O; Cascio, Christopher N; O’Donnell, Matthew Brook; Bingham, C Raymond; Simons-Morton, Bruce; Vettel, Jean M; Falk, Emily B

2018-01-01

Abstract Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt their behavior to fit in with others. We examined whether functional brain connectivity during social exclusion in the fMRI scanner can be used to predict subsequent conformity to peer norms. Adolescent males (n = 57) completed a two-part study on teen driving risk: a social exclusion task (Cyberball) during an fMRI session and a subsequent driving simulator session in which they drove alone and in the presence of a peer who expressed risk-averse or risk-accepting driving norms. We computed the difference in functional connectivity between social exclusion and social inclusion from each node in the brain to nodes in two brain networks, one previously associated with mentalizing (medial prefrontal cortex, temporoparietal junction, precuneus, temporal poles) and another with social pain (dorsal anterior cingulate cortex, anterior insula). Using predictive modeling, this measure of global connectivity during exclusion predicted the extent of conformity to peer pressure during driving in the subsequent experimental session. These findings extend our understanding of how global neural dynamics guide social behavior, revealing functional network activity that captures individual differences. PMID:29529310

Social learning through prediction error in the brain

NASA Astrophysics Data System (ADS)

Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

2017-06-01

Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

Social Anxiety Predicts Aggression in Children with ASD: Clinical Comparisons with Socially Anxious and Oppositional Youth

ERIC Educational Resources Information Center

Pugliese, Cara E.; White, Bradley A.; White, Susan W.; Ollendick, Thomas H.

2013-01-01

The present study examined the degree to which social anxiety predicts aggression in children with high functioning autism spectrum disorders (HFASD, n = 20) compared to children with Social Anxiety Disorder (SAD, n = 20) or with Oppositional Defiant Disorder or Conduct Disorder (ODD/CD, n = 20). As predicted, children with HFASD reported levels…

Computational investigation of kinetics of cross-linking reactions in proteins: importance in structure prediction.

PubMed

Bandyopadhyay, Pradipta; Kuntz, Irwin D

2009-01-01

The determination of protein structure using distance constraints is a new and promising field of study. One implementation involves attaching residues of a protein using a cross-linking agent, followed by protease digestion, analysis of the resulting peptides by mass spectroscopy, and finally sequence threading to detect the protein folds. In the present work, we carry out computational modeling of the kinetics of cross-linking reactions in proteins using the master equation approach. The rate constants of the cross-linking reactions are estimated using the pKas and the solvent-accessible surface areas of the residues involved. This model is tested with fibroblast growth factor (FGF) and cytochrome C. It is consistent with the initial experimental rate data for individual lysine residues for cytochrome C. Our model captures all observed cross-links for FGF and almost 90% of the observed cross-links for cytochrome C, although it also predicts cross-links that were not observed experimentally (false positives). However, the analysis of the false positive results is complicated by the fact that experimental detection of cross-links can be difficult and may depend on specific experimental conditions such as pH, ionic strength. Receiver operator characteristic plots showed that our model does a good job in predicting the observed cross-links. Molecular dynamics simulations showed that for cytochrome C, in general, the two lysines come closer for the observed cross-links as compared to the false positive ones. For FGF, no such clear pattern exists. The kinetic model and MD simulation can be used to study proposed cross-linking protocols.

Thinking while drinking: Fear of negative evaluation predicts drinking behaviors of students with social anxiety.

PubMed

Villarosa-Hurlocker, Margo C; Whitley, Robert B; Capron, Daniel W; Madson, Michael B

2018-03-01

College students with social anxiety disorder experience more alcohol-related negative consequences, regardless of the amount of alcohol they consume. Social anxiety refers to psychological distress and physiological arousal in social situations due to an excessive fear of negative evaluation by others. The current study examined within-group differences in alcohol-related negative consequences of students who met or exceeded clinically-indicated social anxiety symptoms. In particular, we tested a sequential mediation model of the cognitive (i.e., fear of negative evaluation) and behavioral (protective behavioral strategies) mechanisms for the link between social anxiety disorder subtypes (i.e., interaction and performance-type) and alcohol-related negative consequences. Participants were 412 traditional-age college student drinkers who met or exceeded the clinically-indicated threshold for social anxiety disorder and completed measures of fear of negative evaluation, protective behavioral strategies (controlled consumption and serious harm reduction), and alcohol-related negative consequences. Fear of negative evaluation and serious harm reduction strategies sequentially accounted for the relationship between interaction social anxiety disorder and alcohol-related negative consequences, such that students with more severe interaction social anxiety symptoms reported more fear of negative evaluation, which was related to more serious harm reduction strategies, which predicted fewer alcohol-related negative consequences. Future directions and implications are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Core dimensions of personality broadly account for the link from perceived social support to symptoms of depression and anxiety.

PubMed

Lewis, Gary J; Bates, Timothy C; Posthuma, Danielle; Polderman, Tinca J C

2014-08-01

Specific personality traits and poor social support are risk factors for anxiety and depression. Little work, however, has considered the effects of social support and personality on these aspects of psychopathology simultaneously. We examined whether perceived social support mediates the effects of core personality domains on symptoms of anxiety and depression. Measures of personality (based on the Five-Factor Model [FFM]), perceived social support, and symptoms of depression and anxiety were collected in a large Dutch adult population-based sample (n = 555), and, except for depression symptoms, in an independent U.S. adult population-based sample (n = 511). Path modeling was used to test the effects of FFM traits on symptoms of depression and anxiety, with and without the mediation of perceived social support. Social support showed no link to symptoms of anxiety and only modest links to symptoms of depression when controlling for the FFM traits. Neuroticism had the strongest effect on symptoms of both depression and anxiety, with Extraversion also showing links to symptoms of depression. Social support has limited influence on symptoms of depression, and no effects on anxiety, over and above the effects of personality. Links between social support and anxiety/depression may largely reflect influences of Neuroticism and Extraversion. © 2013 Wiley Periodicals, Inc.

Librarians as Advocates of Social Media for Researchers: A Social Media Project Initiated by Linköping University Library, Sweden

ERIC Educational Resources Information Center

Persson, Sassa; Svenningsson, Maria

2016-01-01

Librarians at Linköping University help researchers keep abreast of developments in their fields and to increase the visibility of their work. Strategic, professional use of social media ought to be an essential part of a researcher's communication strategy. This article investigates the level of awareness of the professional use of social media…

OXTR polymorphism predicts social relationships through its effects on social temperament.

PubMed

Creswell, Kasey G; Wright, Aidan G C; Troxel, Wendy M; Ferrell, Robert E; Flory, Janine D; Manuck, Stephen B

2015-06-01

Humans have a fundamental need for strong interpersonal bonds, yet individuals differ appreciably in their degree of social integration. That these differences are also substantially heritable has spurred interest in biological mechanisms underlying the quality and quantity of individuals' social relationships. We propose that polymorphic variation in the oxytocin receptor gene (OXTR) associates with complex social behaviors and social network composition through intermediate effects on negative affectivity and the psychological processing of socially relevant information. We tested a hypothesized social cascade from the molecular level (OXTR variation) to the social environment, through negative affectivity and inhibited sociality, in a sample of 1295 men and women of European American (N = 1081) and African American (N = 214) ancestry. Compared to European Americans having any T allele of rs1042778, individuals homozygous for the alternate G allele reported significantly lower levels of negative affectivity and inhibited sociality, which in turn predicted significantly higher levels of social support and a larger/more diverse social network. Moreover, the effect of rs1042778 variation on social support was fully accounted for by associated differences in negative affectivity and inhibited sociality. Results replicated in the African American sample. Findings suggest that OXTR variation modulates levels of social support via proximal impacts on individual temperament. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Not Just Another Single Issue: Teen Pregnancy Prevention's Link to Other Critical Social Issues.

ERIC Educational Resources Information Center

National Campaign To Prevent Teen Pregnancy, Washington, DC.

This report discusses critical social issues linked to teen pregnancy, explaining that teen pregnancy prevention should be viewed as working to improve these social issues. After providing general background on teen pregnancy, the report offers five fact sheets: (1) "Teen Pregnancy, Welfare Dependency, and Poverty" (continuing to reduce…

Social in, social out: How the brain responds to social language with more social language

PubMed Central

O’Donnell, Matthew Brook; Falk, Emily B.; Lieberman, Matthew D.

2014-01-01

Social connection is a fundamental human need. As such, people’s brains are sensitized to social cues, such as those carried by language, and to promoting social communication. The neural mechanisms of certain key building blocks in this process, such as receptivity to and reproduction of social language, however, are not known. We combined quantitative linguistic analysis and neuroimaging to connect neural activity in brain regions used to simulate the mental states of others with exposure to, and re-transmission of, social language. Our results link findings on successful idea transmission from communication science, sociolinguistics and cognitive neuroscience to prospectively predict the degree of social language that participants utilize when re-transmitting ideas as a function of 1) initial language inputs and 2) neural activity during idea exposure. PMID:27642220

Perceived social pressure not to experience negative emotion is linked to selective attention for negative information.

PubMed

Bastian, Brock; Pe, Madeline Lee; Kuppens, Peter

2017-02-01

Social norms and values may be important predictors of how people engage with and regulate their negative emotional experiences. Previous research has shown that social expectancies (the perceived social pressure not to feel negative emotion (NE)) exacerbate feelings of sadness. In the current research, we examined whether social expectancies may be linked to how people process emotional information. Using a modified classical flanker task involving emotional rather than non-emotional stimuli, we found that, for those who experienced low levels of NE, social expectancies were linked to the selective avoidance of negative emotional information. Those who experienced high levels of NE did not show a selective avoidance of negative emotional information. The findings suggest that, for people who experience many NEs, social expectancies may lead to discrepancies between how they think they ought to feel and the kind of emotional information they pay attention to.

Parental Control of the Time Preadolescents Spend on Social Media: Links with Preadolescents' Social Media Appearance Comparisons and Mental Health.

PubMed

Fardouly, Jasmine; Magson, Natasha R; Johnco, Carly J; Oar, Ella L; Rapee, Ronald M

2018-07-01

Time spent on social media and making online comparisons with others may influence users' mental health. This study examined links between parental control over the time their child spends on social media, preadolescents' time spent browsing social media, preadolescents' appearance comparisons on social media, and preadolescents' appearance satisfaction, depressive symptoms, and life satisfaction. Preadolescent social media users (N = 284, 49.1% female; aged 10-12) and one of their parents completed online surveys. Preadolescents, whose parents reported greater control over their child's time on social media, reported better mental health. This relationship was mediated by preadolescents spending less time browsing and making fewer appearance comparisons on social media. Parental control over time spent on social media may be associated with benefits for mental health among preadolescents.

Performance Prediction of a Synchronization Link for Distributed Aerospace Wireless Systems

PubMed Central

Shao, Huaizong

2013-01-01

For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link. PMID:23970828

Performance prediction of a synchronization link for distributed aerospace wireless systems.

PubMed

Wang, Wen-Qin; Shao, Huaizong

2013-01-01

For reasons of stealth and other operational advantages, distributed aerospace wireless systems have received much attention in recent years. In a distributed aerospace wireless system, since the transmitter and receiver placed on separated platforms which use independent master oscillators, there is no cancellation of low-frequency phase noise as in the monostatic cases. Thus, high accurate time and frequency synchronization techniques are required for distributed wireless systems. The use of a dedicated synchronization link to quantify and compensate oscillator frequency instability is investigated in this paper. With the mathematical statistical models of phase noise, closed-form analytic expressions for the synchronization link performance are derived. The possible error contributions including oscillator, phase-locked loop, and receiver noise are quantified. The link synchronization performance is predicted by utilizing the knowledge of the statistical models, system error contributions, and sampling considerations. Simulation results show that effective synchronization error compensation can be achieved by using this dedicated synchronization link.

Social and Built Environmental Correlates of Predicted Blood Lead Levels in the Flint Water Crisis.

PubMed

Sadler, Richard Casey; LaChance, Jenny; Hanna-Attisha, Mona

2017-05-01

To highlight contextual factors tied to increased blood lead level (BLL) risk following the lead-in-water contamination in Flint, Michigan. Using geocoded BLL data collected in 2013 and 2015 and areal interpolation, we predicted BLLs at every residential parcel in the city. We then spatially joined social and built environmental variables to link the parcels with neighborhood-level factors that may influence BLLs. When we compared levels before and during the water crisis, we saw the highest estimates of predicted BLLs during the water crisis and the greatest changes in BLLs in neighborhoods with the longest water residence time in pipes (μ = 2.30 µg/dL; Δ = 0.45 µg/dL), oldest house age (μ = 2.22 µg/dL; Δ = 0.37 µg/dL), and poorest average neighborhood housing condition (μ = 2.18 µg/dL; Δ = 0.44 µg/dL). Key social and built environmental variables correlate with BLL; such information can continue to guide response by prioritizing older, deteriorating neighborhoods with the longest water residence time in pipes.

Neighborhood linking social capital as a predictor of drug abuse: A Swedish national cohort study.

PubMed

Sundquist, Jan; Sjöstedt, Cecilia; Winkleby, Marilyn; Li, Xinjun; Kendler, Kenneth S; Sundquist, Kristina

2016-12-01

This study examines the association between the incidence of drug abuse (DA) and linking (communal) social capital, a theoretical concept describing the amount of trust between individuals and societal institutions. We present results from an 8-year population-based cohort study that followed all residents in Sweden, aged 15-44, from 2003 through 2010, for a total of 1,700,896 men and 1,642,798 women. Linking social capital was conceptualized as the proportion of people in a geographically defined neighborhood who voted in local government elections. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance. We found robust associations between linking social capital and DA in men and women. For men, the OR for DA in the crude model was 2.11 [95% confidence interval (CI) 2.02-2.21] for those living in neighborhoods with the lowest vs. highest level of social capital. After accounting for neighborhood level deprivation, the OR fell to 1.59 (1.51-1-68). The ORs remained significant after accounting for age, family income, marital status, country of birth, education level, and region of residence, and after further accounting for comorbidities and family history of comorbidities and family history of DA. For women, the OR decreased from 2.15 (2.03-2.27) in the crude model to 1.31 (1.22-1.40) in the final model, adjusted for multiple neighborhood-level, individual-level variables, and family history for DA. Our study suggests that low linking social capital may have significant independent effects on DA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neighborhood linking social capital as a predictor of drug abuse: A Swedish national cohort study

PubMed Central

Sundquist, Jan; Sjöstedt, Cecilia; Winkleby, Marilyn; Li, Xinjun; Kendler, Kenneth S.; Sundquist, Kristina

2016-01-01

Aims This study examines the association between the incidence of drug abuse (DA) and linking (communal) social capital, a theoretical concept describing the amount of trust between individuals and societal institutions. Methods We present results from an 8-year population-based cohort study that followed all residents in Sweden, aged 15–44, from 2003 through 2010, for a total of 1,700,896 men and 1,642,798 women. Linking social capital was conceptualized as the proportion of people in a geographically defined neighborhood who voted in local government elections. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance. Results We found robust associations between linking social capital and DA in men and women. For men, the OR for DA in the crude model was 2.11 [95% confidence interval (CI) 2.02–2.21] for those living in neighborhoods with the lowest vs. highest level of social capital. After accounting for neighborhood level deprivation, the OR fell to 1.59 (1.51–1-68). The ORs remained significant after accounting for age, family income, marital status, country of birth, education level, and region of residence, and after further accounting for comorbidities and family history of comorbidities and family history of DA. For women, the OR decreased from 2.15 (2.03–2.27) in the crude model to 1.31 (1.22–1.40) in the final model, adjusted for multiple neighborhood-level, individual-level variables, and family history for DA. Conclusions Our study suggests that low linking social capital may have significant independent effects on DA. PMID:27416013

Predicting Drop-Out from Social Behaviour of Students

ERIC Educational Resources Information Center

Bayer, Jaroslav; Bydzovska, Hana; Geryk, Jan; Obsivac, Tomas; Popelinsky, Lubomir

2012-01-01

This paper focuses on predicting drop-outs and school failures when student data has been enriched with data derived from students social behaviour. These data describe social dependencies gathered from e-mail and discussion board conversations, among other sources. We describe an extraction of new features from both student data and behaviour…

Design and Implementation of Davis Social Links OSN Kernel

NASA Astrophysics Data System (ADS)

Tran, Thomas; Chan, Kelcey; Ye, Shaozhi; Bhattacharyya, Prantik; Garg, Ankush; Lu, Xiaoming; Wu, S. Felix

Social network popularity continues to rise as they broaden out to more users. Hidden away within these social networks is a valuable set of data that outlines everyone’s relationships. Networks have created APIs such as the Facebook Development Platform and OpenSocial that allow developers to create applications that can leverage user information. However, at the current stage, the social network support for these new applications is fairly limited in its functionality. Most, if not all, of the existing internet applications such as email, BitTorrent, and Skype cannot benefit from the valuable social network among their own users. In this paper, we present an architecture that couples two different communication layers together: the end2end communication layer and the social context layer, under the Davis Social Links (DSL) project. Our proposed architecture attempts to preserve the original application semantics (i.e., we can use Thunderbird or Outlook, unmodified, to read our SMTP emails) and provides the communicating parties (email sender and receivers) a social context for control and management. For instance, the receiver can set trust policy rules based on the social context between the pair, to determine how a particular email in question should be prioritized for delivery to the SMTP layer. Furthermore, as our architecture includes two coupling layers, it is then possible, as an option, to shift some of the services from the original applications into the social context layer. In the context of email, for example, our architecture allows users to choose operations, such as reply, reply-all, and forward, to be realized in either the application layer or the social network layer. And, the realization of these operations under the social network layer offers powerful features unavailable in the original applications. To validate our coupling architecture, we have implemented a DSL kernel prototype as a Facebook application called CyrusDSL (currently about

Ophthalmology on social networking sites: an observational study of Facebook, Twitter, and LinkedIn.

PubMed

Micieli, Jonathan A; Tsui, Edmund

2015-01-01

The use of social media in ophthalmology remains largely unknown. Our aim was to evaluate the extent and involvement of ophthalmology journals, professional associations, trade publications, and patient advocacy and fundraising groups on social networking sites. An archived list of 107 ophthalmology journals from SCImago, trade publications, professional ophthalmology associations, and patient advocacy organizations were searched for their presence on Facebook, Twitter, and LinkedIn. Activity and popularity of each account was quantified by using the number of "likes" on Facebook, the number of followers on Twitter, and members on LinkedIn. Of the 107 journals ranked by SCImago, 21.5% were present on Facebook and 18.7% were present on Twitter. Journal of Community Eye Health was the most popular on Facebook and JAMA Ophthalmology was most popular on Twitter. Among the 133 members of the International Council of Ophthalmology, 17.3% were present on Facebook, 12.8% were present on Twitter, and 7.5% were present on LinkedIn. The most popular on Facebook was the International Council of Ophthalmology, and the American Academy of Ophthalmology was most popular on Twitter and LinkedIn. Patient advocacy organizations were more popular on all sites compared with journals, professional association, and trade publications. Among the top ten most popular pages in each category, patient advocacy groups were most active followed by trade publications, professional associations, and journals. Patient advocacy groups lead the way in social networking followed by professional organizations and journals. Although some journals use social media, most have yet to engage its full potential and maximize the number of potential interested individuals.

Ophthalmology on social networking sites: an observational study of Facebook, Twitter, and LinkedIn

PubMed Central

Micieli, Jonathan A; Tsui, Edmund

2015-01-01

Background The use of social media in ophthalmology remains largely unknown. Our aim was to evaluate the extent and involvement of ophthalmology journals, professional associations, trade publications, and patient advocacy and fundraising groups on social networking sites. Methods An archived list of 107 ophthalmology journals from SCImago, trade publications, professional ophthalmology associations, and patient advocacy organizations were searched for their presence on Facebook, Twitter, and LinkedIn. Activity and popularity of each account was quantified by using the number of “likes” on Facebook, the number of followers on Twitter, and members on LinkedIn. Results Of the 107 journals ranked by SCImago, 21.5% were present on Facebook and 18.7% were present on Twitter. Journal of Community Eye Health was the most popular on Facebook and JAMA Ophthalmology was most popular on Twitter. Among the 133 members of the International Council of Ophthalmology, 17.3% were present on Facebook, 12.8% were present on Twitter, and 7.5% were present on LinkedIn. The most popular on Facebook was the International Council of Ophthalmology, and the American Academy of Ophthalmology was most popular on Twitter and LinkedIn. Patient advocacy organizations were more popular on all sites compared with journals, professional association, and trade publications. Among the top ten most popular pages in each category, patient advocacy groups were most active followed by trade publications, professional associations, and journals. Conclusion Patient advocacy groups lead the way in social networking followed by professional organizations and journals. Although some journals use social media, most have yet to engage its full potential and maximize the number of potential interested individuals. PMID:25709390

Prediction is Production: The missing link between language production and comprehension.

PubMed

Martin, Clara D; Branzi, Francesca M; Bar, Moshe

2018-01-18

Language comprehension often involves the generation of predictions. It has been hypothesized that such prediction-for-comprehension entails actual language production. Recent studies provided evidence that the production system is recruited during language comprehension, but the link between production and prediction during comprehension remains hypothetical. Here, we tested this hypothesis by comparing prediction during sentence comprehension (primary task) in participants having the production system either available or not (non-verbal versus verbal secondary task). In the primary task, sentences containing an expected or unexpected target noun-phrase were presented during electroencephalography recording. Prediction, measured as the magnitude of the N400 effect elicited by the article (expected versus unexpected), was hindered only when the production system was taxed during sentence context reading. The present study provides the first direct evidence that the availability of the speech production system is necessary for generating lexical prediction during sentence comprehension. Furthermore, these important results provide an explanation for the recruitment of language production during comprehension.

c-Fos expression predicts long-term social memory retrieval in mice.

PubMed

Lüscher Dias, Thomaz; Fernandes Golino, Hudson; Moura de Oliveira, Vinícius Elias; Dutra Moraes, Márcio Flávio; Schenatto Pereira, Grace

2016-10-15

The way the rodent brain generally processes socially relevant information is rather well understood. How social information is stored into long-term social memory, however, is still under debate. Here, brain c-Fos expression was measured after adult mice were exposed to familiar or novel juveniles and expression was compared in several memory and socially relevant brain areas. Machine Learning algorithm Random Forest was then used to predict the social interaction category of adult mice based on c-Fos expression in these areas. Interaction with a familiar co-specific altered brain activation in the olfactory bulb, amygdala, hippocampus, lateral septum and medial prefrontal cortex. Remarkably, Random Forest was able to predict interaction with a familiar juvenile with 100% accuracy. Activity in the olfactory bulb, amygdala, hippocampus and the medial prefrontal cortex were crucial to this prediction. From our results, we suggest long-term social memory depends on initial social olfactory processing in the medial amygdala and its output connections synergistically with non-social contextual integration by the hippocampus and medial prefrontal cortex top-down modulation of primary olfactory structures. Copyright © 2016 Elsevier B.V. All rights reserved.

The brain, self and society: a social-neuroscience model of predictive processing.

PubMed

Kelly, Michael P; Kriznik, Natasha M; Kinmonth, Ann Louise; Fletcher, Paul C

2018-05-10

This paper presents a hypothesis about how social interactions shape and influence predictive processing in the brain. The paper integrates concepts from neuroscience and sociology where a gulf presently exists between the ways that each describe the same phenomenon - how the social world is engaged with by thinking humans. We combine the concepts of predictive processing models (also called predictive coding models in the neuroscience literature) with ideal types, typifications and social practice - concepts from the sociological literature. This generates a unified hypothetical framework integrating the social world and hypothesised brain processes. The hypothesis combines aspects of neuroscience and psychology with social theory to show how social behaviors may be "mapped" onto brain processes. It outlines a conceptual framework that connects the two disciplines and that may enable creative dialogue and potential future research.

Post-event Processing Predicts Impaired Cortisol Recovery Following Social Stressor: The Moderating Role of Social Anxiety.

PubMed

Maeda, Shunta; Sato, Tomoya; Shimada, Hironori; Tsumura, Hideki

2017-01-01

There is growing evidence that individuals with social anxiety show impaired cortisol recovery after experiencing social evaluative stressors. Yet, little is known regarding the cognitive processes underlying such impaired cortisol recovery. The present study examined the effect of post-event processing (PEP), referred to as repetitive thinking about social situations, on cortisol recovery following a social stressor. Forty-two non-clinical university students (23 women, 19 men, mean age = 22.0 ± 2.0 years) completed the Trier Social Stress Test (TSST), followed by a thought sampling procedure which assessed the frequency of PEP reflecting the TSST. A growth curve model showed PEP and social anxiety interactively predicted cortisol recovery. In particular, PEP predicted impaired cortisol recovery in those with low levels of social anxiety but not in those with high levels of social anxiety, which contradicted the initial hypothesis. These findings suggest that PEP is differentially associated with cortisol recovery depending on levels of social anxiety. The possible mechanisms underlying these findings were discussed in terms of protective inhibition framework.

Bonding, Bridging, and Linking Social Capital and Self-Rated Health among Chinese Adults: Use of the Anchoring Vignettes Technique.

PubMed

Chen, He; Meng, Tianguang

2015-01-01

Three main opposing camps exist over how social capital relates to population health, namely the social support perspective, the inequality thesis, and the political economy approach. The distinction among bonding, bridging, and linking social capital probably helps close the debates between these three camps, which is rarely investigated in existing literatures. Moreover, although self-rated health is a frequently used health indicator in studies on the relationship between social capital and health, the interpersonal incomparability of this measure has been largely neglected. This study has two main objectives. Firstly, we aim to investigate the relationship between bonding, bridging, and linking social capital and self-rated health among Chinese adults. Secondly, we aim to improve the interpersonal comparability in self-rated health measurement. We use data from a nationally representative survey in China. Self-rated health was adjusted using the anchoring vignettes technique to improve comparability. Two-level ordinal logistic regression was performed to model the association between social capital and self-rated health at both individual and community levels. The interaction between residence and social capital was included to examine urban/rural disparities in the relationship. We found that most social capital indicators had a significant relationship with adjusted self-rated health of Chinese adults, but the relationships were mixed. Individual-level bonding, linking social capital, and community-level bridging social capital were positively related with health. Significant urban/rural disparities appeared in the association between community-level bonding, linking social capital, and adjusted self-rated health. For example, people living in communities with higher bonding social capital tended to report poorer adjusted self-rated health in urban areas, but the opposite tendency held for rural areas. Furthermore, the comparison between multivariate analyses

Bonding, Bridging, and Linking Social Capital and Self-Rated Health among Chinese Adults: Use of the Anchoring Vignettes Technique

PubMed Central

Chen, He; Meng, Tianguang

2015-01-01

Three main opposing camps exist over how social capital relates to population health, namely the social support perspective, the inequality thesis, and the political economy approach. The distinction among bonding, bridging, and linking social capital probably helps close the debates between these three camps, which is rarely investigated in existing literatures. Moreover, although self-rated health is a frequently used health indicator in studies on the relationship between social capital and health, the interpersonal incomparability of this measure has been largely neglected. This study has two main objectives. Firstly, we aim to investigate the relationship between bonding, bridging, and linking social capital and self-rated health among Chinese adults. Secondly, we aim to improve the interpersonal comparability in self-rated health measurement. We use data from a nationally representative survey in China. Self-rated health was adjusted using the anchoring vignettes technique to improve comparability. Two-level ordinal logistic regression was performed to model the association between social capital and self-rated health at both individual and community levels. The interaction between residence and social capital was included to examine urban/rural disparities in the relationship. We found that most social capital indicators had a significant relationship with adjusted self-rated health of Chinese adults, but the relationships were mixed. Individual-level bonding, linking social capital, and community-level bridging social capital were positively related with health. Significant urban/rural disparities appeared in the association between community-level bonding, linking social capital, and adjusted self-rated health. For example, people living in communities with higher bonding social capital tended to report poorer adjusted self-rated health in urban areas, but the opposite tendency held for rural areas. Furthermore, the comparison between multivariate analyses

Toward Predicting Popularity of Social Marketing Messages

NASA Astrophysics Data System (ADS)

Yu, Bei; Chen, Miao; Kwok, Linchi

Popularity of social marketing messages indicates the effectiveness of the corresponding marketing strategies. This research aims to discover the characteristics of social marketing messages that contribute to different level of popularity. Using messages posted by a sample of restaurants on Facebook as a case study, we measured the message popularity by the number of "likes" voted by fans, and examined the relationship between the message popularity and two properties of the messages: (1) content, and (2) media type. Combining a number of text mining and statistics methods, we have discovered some interesting patterns correlated to "more popular" and "less popular" social marketing messages. This work lays foundation for building computational models to predict the popularity of social marketing messages in the future.

Social networks predict selective observation and information spread in ravens

PubMed Central

Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

2016-01-01

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

Virality Prediction and Community Structure in Social Networks

NASA Astrophysics Data System (ADS)

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-08-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Virality Prediction and Community Structure in Social Networks

PubMed Central

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-01-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106

Virality prediction and community structure in social networks.

PubMed

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-01-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Social anxiety and eating disorder comorbidity: The role of negative social evaluation fears

PubMed Central

Levinson, Cheri A.; Rodebaugh, Thomas L.

2011-01-01

Social anxiety and eating disorders are highly comorbid. However, it is unknown how specific domains of social anxiety relate to disordered eating. We provide data on these relationships and investigate social appearance anxiety and fear of negative evaluation as potential vulnerabilities linking social anxiety with eating disorders. Specifically, we examined five domains of social anxiety: Social interaction anxiety, fear of scrutiny, fear of positive evaluation, fear of negative evaluation, and social appearance anxiety. Results indicated that social appearance anxiety predicted body dissatisfaction, bulimia symptoms, shape concern, weight concern, and eating concern over and above fear of scrutiny, social interaction anxiety, and fear of positive evaluation. Fear of negative evaluation uniquely predicted drive for thinness and restraint. Structural equation modeling supported a model in which social appearance anxiety and fear of negative evaluation are vulnerabilities for both social anxiety and eating disorder symptoms. Interventions that target these negative social evaluation fears may help prevent development of eating disorders. PMID:22177392

Social anxiety and eating disorder comorbidity: the role of negative social evaluation fears.

PubMed

Levinson, Cheri A; Rodebaugh, Thomas L

2012-01-01

Social anxiety and eating disorders are highly comorbid. However, it is unknown how specific domains of social anxiety relate to disordered eating. We provide data on these relationships and investigate social appearance anxiety and fear of negative evaluation as potential vulnerabilities linking social anxiety with disordered eating. Specifically, we examined five domains of social anxiety: Social interaction anxiety, fear of scrutiny, fear of positive evaluation, fear of negative evaluation, and social appearance anxiety. Results indicated that social appearance anxiety predicted body dissatisfaction, bulimic symptoms, shape concern, weight concern, and eating concern over and above fear of scrutiny, social interaction anxiety, and fear of positive evaluation. Fear of negative evaluation uniquely predicted drive for thinness and restraint. Structural equation modeling supported a model in which social appearance anxiety and fear of negative evaluation are vulnerabilities for both social anxiety and eating disorder symptoms. Interventions that target these negative social evaluation fears may help prevent development of eating disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Construction of a linked health and social care database resource--lessons on process, content and culture.

PubMed

Witham, Miles D; Frost, Helen; McMurdo, Marion; Donnan, Peter T; McGilchrist, Mark

2015-01-01

Combining routinely collected health and social care data on older people is essential to advance both service delivery and research for this client group. Little data is available on how to combine health and social care data; this article provides an overview of a successful data linkage process and discusses potential barriers to executing such projects. We successfully obtained and linked data on older people within Dundee from three sources: Dundee Social Work Department database (30,000 individuals aged 65 years and over), healthcare data held on NHS Tayside patients by the Health Informatics Centre (400,000 individuals), Dundee, and the Dundee of Medicine for the Elderly rehabilitation database (4300 individuals). Data were linked, anonymized and transferred to a Safe Haven environment to ensuring confidentiality and strict access control. Challenges were faced around workflows, culture and documentation. Exploiting the resultant data set raises further challenges centered on database documentation, understanding the way data were collected, dealing with missing data, data validity and collection at different time periods. Routinely collected health and social care data sets can be linked, but significant process barriers must be overcome to allow successful linkage and integration of data and its full exploitation.

Psychological Pathways Linking Social Support to Health Outcomes: A Visit with the “Ghosts” of Research Past, Present, and Future

PubMed Central

Uchino, Bert N.; Bowen, Kimberly; Carlisle, McKenzie; Birmingham, Wendy

2012-01-01

Contemporary models postulate the importance of psychological mechanisms linking perceived and received social support to physical health outcomes. In this review, we examine studies that directly tested the potential psychological mechanisms responsible for links between social support and health-relevant physiological processes (1980s to 2010). Inconsistent with existing theoretical models, no evidence was found that psychological mechanisms such as depression, perceived stress, and other affective processes are directly responsible for links between support and health. We discuss the importance of considering statistical/design issues, emerging conceptual perspectives, and limitations of our existing models for future research aimed at elucidating the psychological mechanisms responsible for links between social support and physical health outcomes. PMID:22326104

Expectancy bias mediates the link between social anxiety and memory bias for social evaluation

PubMed Central

Caouette, Justin D.; Ruiz, Sarah K.; Lee, Clinton C.; Anbari, Zainab; Schriber, Roberta A.; Guyer, Amanda E.

2014-01-01

Social anxiety (SA) involves a multitude of cognitive symptoms related to fear of evaluation, including expectancy and memory biases. We examined whether memory biases are influenced by expectancy biases for social feedback in SA. We hypothesized that, faced with a socially evaluative event, people with higher SA would show a negative expectancy bias for future feedback. Furthermore, we predicted that memory bias for feedback in SA would be mediated by expectancy bias. Ninety-four undergraduate students (55 women, mean age = 19.76 years) underwent a two-visit task that measured expectations about (Visit 1) and memory of (Visit 2) feedback from unknown peers. Results showed that higher levels of SA were associated with negative expectancy bias. An indirect relationship was found between SA and memory bias that was mediated by expectancy bias. The results suggest that expectancy biases are in the causal path from SA to negative memory biases for social evaluation. PMID:25252925

Boldness predicts social status in zebrafish (Danio rerio).

PubMed

Dahlbom, S Josefin; Lagman, David; Lundstedt-Enkel, Katrin; Sundström, L Fredrik; Winberg, Svante

2011-01-01

This study explored if boldness could be used to predict social status. First, boldness was assessed by monitoring individual zebrafish behaviour in (1) an unfamiliar barren environment with no shelter (open field), (2) the same environment when a roof was introduced as a shelter, and (3) when the roof was removed and an unfamiliar object (Lego® brick) was introduced. Next, after a resting period of minimum one week, social status of the fish was determined in a dyadic contest and dominant/subordinate individuals were determined as the winner/loser of two consecutive contests. Multivariate data analyses showed that males were bolder than females and that the behaviours expressed by the fish during the boldness tests could be used to predict which fish would later become dominant and subordinate in the ensuing dyadic contest. We conclude that bold behaviour is positively correlated to dominance in zebrafish and that boldness is not solely a consequence of social dominance.

Boldness Predicts Social Status in Zebrafish (Danio rerio)

PubMed Central

Dahlbom, S. Josefin; Lagman, David; Lundstedt-Enkel, Katrin; Sundström, L. Fredrik; Winberg, Svante

2011-01-01

This study explored if boldness could be used to predict social status. First, boldness was assessed by monitoring individual zebrafish behaviour in (1) an unfamiliar barren environment with no shelter (open field), (2) the same environment when a roof was introduced as a shelter, and (3) when the roof was removed and an unfamiliar object (Lego® brick) was introduced. Next, after a resting period of minimum one week, social status of the fish was determined in a dyadic contest and dominant/subordinate individuals were determined as the winner/loser of two consecutive contests. Multivariate data analyses showed that males were bolder than females and that the behaviours expressed by the fish during the boldness tests could be used to predict which fish would later become dominant and subordinate in the ensuing dyadic contest. We conclude that bold behaviour is positively correlated to dominance in zebrafish and that boldness is not solely a consequence of social dominance. PMID:21858168

An Interpersonal Circumplex Model of Children's Social Goals: Links with Peer-Reported Behavior and Sociometric Status

ERIC Educational Resources Information Center

Ojanen, Tiina; Gronroos, Matti; Salmivalli, Christina

2005-01-01

The objective of the present research was to develop an assessment model for children's social goals. The aims were (a) to fit children's social goals to a circumplex model and to examine links between goals and peer-reported social behaviors (aggression, withdrawal, and prosocial behavior) in a sample of 276 participants (134 girls, 11- to…

Function and structure in social brain regions can link oxytocin-receptor genes with autistic social behavior.

PubMed

Yamasue, Hidenori

2013-02-01

Difficulties in appropriate social and communicative behaviors are the most prevalent and core symptoms of autism spectrum disorders (ASDs). Although recent intensive research has focused on the neurobiological background of these difficulties, many aspects of them were not yet elucidated. Recent studies have employed multimodal magnetic resonance imaging (MRI) indices as intermediate phenotypes of this behavioral phenotype to link candidate genes with the autistic social difficulty. As MRI indices, functional MRI (fMRI), structural MRI, and MR-spectroscopy have been examined in subjects with autism spectrum disorders. As candidate genes, this mini-review has much interest in oxytocin-receptor genes (OXTR), since recent studies have repeatedly reported their associations with normal variations in social cognition and behavior as well as with their extremes, autistic social dysfunction. Through previous increasing studies, medial prefrontal cortex, hypothalamus and amygdala have repeatedly been revealed as neural correlates of autistic social behavior by MRI multimodalities and their relationship to OXTR. For further development of this research area, this mini-review integrates recent accumulating evidence about human behavioral and neural correlates of OXTR. Copyright © 2012 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Social factors predictive of social integration for adults with brain injury.

PubMed

Batchos, Elisabeth; Easton, Amanda; Haak, Christopher; Ditchman, Nicole

2018-08-01

Individuals with acquired brain injury (ABI) may not only struggle with physical and cognitive impairments, but may also face challenges reintegrating into the community socially. Research has demonstrated that following ABI, individuals' social networks tend to dwindle, support may decline, and isolation increases. This study examined factors impacting social integration in a community-based sample of 102 individuals with ABI. Potential predictors included emotional support, instrumental support, problem solving confidence, and approach-avoidance style (AAS) of problem solving, while controlling for age, gender, education, and time since injury. Hierarchical regression was used to analyze whether these factors were predictive of social integration. The final model accounted for 33% of the variance in social integration outcomes. Results demonstrated that emotional support was initially a significant predictor; however, when controlling for emotional support the variance in social integration was better accounted for by social problem solving - specifically, AAS. A follow-up mediation analysis indicated that the relationship between social problem solving (specifically, AAS) and social integration was partially mediated by emotional support. This suggests that for individuals with ABI, a tendency to approach rather than avoid social problem solving issues is a significant predictor for social integration both directly and indirectly through its association with emotional social support. Implications for Rehabilitation Both instrumental and emotional social support should be assessed in patients with acquired brain injury (ABI), ensuring that emotional needs are met in addition to the more obvious instrumental needs. Barriers to problem solving for people with ABI may limit optimal social integration; thus, assessment and intervention aimed at increasing AAS are recommended. To enhance the social integration outcomes of people with brain injury, strength

The role of social support, family identification, and family constraints in predicting posttraumatic stress after cancer.

PubMed

Swartzman, Samantha; Sani, Fabio; Munro, Alastair J

2017-09-01

We compared social support with other potential psychosocial predictors of posttraumatic stress after cancer. These included family identification, or a sense of belonging to and commonality with family members, and family constraints, or the extent to which family members are closed, judgmental, or unreceptive in conversations about cancer. We also tested the hypothesis that family constraints mediate the relationship between family identification and cancer-related posttraumatic stress. We used a cross-sectional design. Surveys were collected from 205 colorectal cancer survivors in Tayside, Scotland. Both family identification and family constraints were stronger independent predictors of posttraumatic stress than social support. In multivariate analyses, social support was not a significant independent predictor of posttraumatic stress. In addition, there was a significant indirect effect of family identification on posttraumatic stress through family constraints. Numerous studies demonstrate a link between social support and posttraumatic stress. However, experiences within the family may be more important in predicting posttraumatic stress after cancer. Furthermore, a sense of belonging to and commonality with the family may reduce the extent to which cancer survivors experience constraints on conversations about cancer; this may, in turn, reduce posttraumatic stress. Copyright © 2016 John Wiley & Sons, Ltd.

Is social engagement linked to body image and depression among aging women?

PubMed

Sabik, Natalie J

2017-01-01

Maintaining an active and engaged social life is a critical component of aging well, and women are generally more socially active than men. However, as women age their self-perceptions of their bodies may reduce social behaviors and consequently, increase depressive symptoms. Because little is known about how body image is associated with social engagement and depressive symptoms among aging women, four aspects of body image: satisfaction with cosmetic features, body function, physical appearance, and weight were assessed among women aged 65 and older (n = 123). Regression analyses indicated that cosmetic appearance, body function, and physical appearance were associated with depressive symptoms, whereas satisfaction with weight was unrelated. Further, both greater satisfaction with cosmetic features and body function were associated with higher levels of social engagement, and social engagement mediated the association between these aspects of body satisfaction and depressive symptoms. The findings indicate that specific age-relevant aspects of body satisfaction are linked to social behavior and depression among aging women, and reduced body satisfaction may lead to lower social engagement, and consequently aging women's health and well-being may be diminished.

Using social media as a tool to predict syphilis.

PubMed

Young, Sean D; Mercer, Neil; Weiss, Robert E; Torrone, Elizabeth A; Aral, Sevgi O

2018-04-01

Syphilis rates have been rapidly rising in the United States. New technologies, such as social media, might be used to anticipate and prevent the spread of disease. Because social media data collection is easy and inexpensive, integration of social media data into syphilis surveillance may be a cost-effective surveillance strategy, especially in low-resource regions. People are increasingly using social media to discuss health-related issues, such as sexual risk behaviors, allowing social media to be a potential tool for public health and medical research. This study mined Twitter data to assess whether social media could be used to predict syphilis cases in 2013 based on 2012 data. We collected 2012 and 2013 county-level primary and secondary (P&S) and early latent syphilis cases reported to the Center for Disease Control and Prevention, along with >8500 geolocated tweets in the United States that were filtered to include sexual risk-related keywords, including colloquial terms for intercourse. We assessed the relationship between syphilis-related tweets and actual case reports by county, controlling for socioeconomic indicators and prior year syphilis cases. We found a significant positive relationship between tweets and cases of P&S and early latent syphilis. This study shows that social media may be an additional tool to enhance syphilis prediction and surveillance. Copyright © 2017 Elsevier Inc. All rights reserved.

Social Networking Site Use Predicts Changes in Young Adults’ Psychological Adjustment

PubMed Central

Szwedo, David E.; Mikami, Amori Yee; Allen, Joseph P.

2012-01-01

This study examined youths’ friendships and posted pictures on social networking sites as predictors of changes in their adjustment over time. Observational, self-report, and peer report data were obtained from a community sample of 89 young adults interviewed at age 21 and again at age 22. Findings were consistent with a leveling effect for online friendships, predicting decreases in internalizing symptoms for youth with lower initial levels of social acceptance, but increases in symptoms for youth with higher initial levels over the following year. Across the entire sample, deviant behavior in posted photos predicted increases in young adults’ problematic alcohol use over time. The importance of considering the interplay between online and offline social factors for predicting adjustment is discussed. PMID:23109797

External immunity in ant societies: sociality and colony size do not predict investment in antimicrobials

PubMed Central

Halawani, Omar; Pearson, Bria; Mathews, Stephanie; López-Uribe, Margarita M.; Dunn, Robert R.; Smith, Adrian A.

2018-01-01

Social insects live in dense groups with a high probability of disease transmission and have therefore faced strong pressures to develop defences against pathogens. For this reason, social insects have been hypothesized to invest in antimicrobial secretions as a mechanism of external immunity to prevent the spread of disease. However, empirical studies linking the evolution of sociality with increased investment in antimicrobials have been relatively few. Here we quantify the strength of antimicrobial secretions among 20 ant species that cover a broad spectrum of ant diversity and colony sizes. We extracted external compounds from ant workers to test whether they inhibited the growth of the bacterium Staphylococcus epidermidis. Because all ant species are highly social, we predicted that all species would exhibit some antimicrobial activity and that species that form the largest colonies would exhibit the strongest antimicrobial response. Our comparative approach revealed that strong surface antimicrobials are common to particular ant clades, but 40% of species exhibited no antimicrobial activity at all. We also found no correlation between antimicrobial activity and colony size. Rather than relying on antimicrobial secretions as external immunity to control pathogen spread, many ant species have probably developed alternative strategies to defend against disease pressure. PMID:29515850

Attachment's Links With Adolescents' Social Emotions: The Roles of Negative Emotionality and Emotion Regulation.

PubMed

Murphy, Tia Panfile; Laible, Deborah J; Augustine, Mairin; Robeson, Lindsay

2015-01-01

Recent research has attempted to explain the mechanisms through which parental attachment affects social and emotional outcomes (e.g., Burnette, Taylor, Worthington, & Forsyth, 2007 ; Panfile & Laible, 2012 ). The authors' goal was to examine negative emotionality and emotion regulation as mediators of the associations that attachment has with empathy, forgiveness, guilt, and jealousy. One hundred forty-eight adolescents reported their parental attachment security, general levels of negative emotionality and abilities to regulate emotional responses, and tendencies to feel empathy, forgiveness, guilt, and jealousy. Results revealed that attachment security was associated with higher levels of empathy, forgiveness, and guilt, but lower levels of jealousy. In addition, emotion regulation mediated the links attachment shared with both empathy and guilt, such that higher levels of attachment security were linked with greater levels of emotion regulation, which led to greater levels of empathy and guilt. Alternatively, negative emotionality mediated the links attachment shared with both forgiveness and jealousy, such that higher levels of attachment security were associated with lower levels of negative emotionality, which in turn was linked to lower levels of forgiveness and higher levels of jealousy. This study provides a general picture of how attachment security may play a role in shaping an individual's levels of social emotions.

Social Media Social Comparison of Ability (but not Opinion) Predicts Lower Identity Clarity: Identity Processing Style as a Mediator.

PubMed

Yang, Chia-Chen; Holden, Sean M; Carter, Mollie D K

2018-01-11

Social comparison on social media has received increasing attention, but most research has focused on one type of social comparison and its psycho-emotional implications. Little is known about how different types of social comparison influence youth's identity development. Drawing on the theories of identity processing styles and social comparison, we examined how two different forms of social comparison on social media related to three identity processing styles, which in turn predicted youth's global self-esteem and identity clarity. We surveyed 219 college freshmen (M age  = 18.29; 74% female) once in the Fall and once in the Spring. Social comparison of ability on social media was related to concurrent diffuse-avoidant identity processing style, which predicted lower identity clarity months later. In contrast, social comparison of opinion on social media did not influence college freshmen's global self-esteem and identity clarity through identity processing styles. The findings clarified the implications of online social comparison for youth's identity development.

Neuronal prediction of opponent's behavior during cooperative social interchange in primates.

PubMed

Haroush, Keren; Williams, Ziv M

2015-03-12

A cornerstone of successful social interchange is the ability to anticipate each other's intentions or actions. While generating these internal predictions is essential for constructive social behavior, their single neuronal basis and causal underpinnings are unknown. Here, we discover specific neurons in the primate dorsal anterior cingulate that selectively predict an opponent's yet unknown decision to invest in their common good or defect and distinct neurons that encode the monkey's own current decision based on prior outcomes. Mixed population predictions of the other was remarkably near optimal compared to behavioral decoders. Moreover, disrupting cingulate activity selectively biased mutually beneficial interactions between the monkeys but, surprisingly, had no influence on their decisions when no net-positive outcome was possible. These findings identify a group of other-predictive neurons in the primate anterior cingulate essential for enacting cooperative interactions and may pave a way toward the targeted treatment of social behavioral disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

Precision and negative predictive value of links between ClinicalTrials.gov and PubMed.

PubMed

Huser, Vojtech; Cimino, James J

2012-01-01

One of the goals of translational science is to shorten the time from discovery to clinical use. Clinical trial registries were established to increase transparency in completed and ongoing clinical trials, and they support linking trials with resulting publications. We set out to investigate precision and negative predictive value (NPV) of links between ClinicalTrials.gov (CT.gov) and PubMed. CT.gov has been established to increase transparency in clinical trials and the link to PubMed is crucial for supporting a number of important functions, including ascertaining publication bias. We drew a random sample of trials downloaded from CT.gov and performed manual review of retrieved publications. We characterize two types of links between trials and publications (NCT-link originating from MEDLINE and PMID-link originating from CT.gov).The link precision is different based on type (NCT-link: 100%; PMID-link: 63% to 96%). In trials with no linked publication, we were able to find publications 44% of the time (NPV=56%) by searching PubMed. This low NPV shows that there are potentially numerous publications that should have been formally linked with the trials. Our results indicate that existing trial registry and publisher policies may not be fully enforced. We suggest some automated methods for improving link quality.

Does workplace social capital protect against long-term sickness absence? Linking workplace aggregated social capital to sickness absence registry data.

PubMed

Hansen, Anne-Sophie K; Madsen, Ida E H; Thorsen, Sannie Vester; Melkevik, Ole; Bjørner, Jakob Bue; Andersen, Ingelise; Rugulies, Reiner

2018-05-01

Most previous prospective studies have examined workplace social capital as a resource of the individual. However, literature suggests that social capital is a collective good. In the present study we examined whether a high level of workplace aggregated social capital (WASC) predicts a decreased risk of individual-level long-term sickness absence (LTSA) in Danish private sector employees. A sample of 2043 employees (aged 18-64 years, 38.5% women) from 260 Danish private-sector companies filled in a questionnaire on workplace social capital and covariates. WASC was calculated by assigning the company-averaged social capital score to all employees of each company. We derived LTSA, defined as sickness absence of more than three weeks, from a national register. We examined if WASC predicted employee LTSA using multilevel survival analyses, while excluding participants with LTSA in the three months preceding baseline. We found no statistically significant association in any of the analyses. The hazard ratio for LTSA in the fully adjusted model was 0.93 (95% CI 0.77-1.13) per one standard deviation increase in WASC. When using WASC as a categorical exposure we found a statistically non-significant tendency towards a decreased risk of LTSA in employees with medium WASC (fully adjusted model: HR 0.78 (95% CI 0.48-1.27)). Post hoc analyses with workplace social capital as a resource of the individual showed similar results. WASC did not predict LTSA in this sample of Danish private-sector employees.

An Integrated Children Disease Prediction Tool within a Special Social Network.

PubMed

Apostolova Trpkovska, Marika; Yildirim Yayilgan, Sule; Besimi, Adrian

2016-01-01

This paper proposes a social network with an integrated children disease prediction system developed by the use of the specially designed Children General Disease Ontology (CGDO). This ontology consists of children diseases and their relationship with symptoms and Semantic Web Rule Language (SWRL rules) that are specially designed for predicting diseases. The prediction process starts by filling data about the appeared signs and symptoms by the user which are after that mapped with the CGDO ontology. Once the data are mapped, the prediction results are presented. The phase of prediction executes the rules which extract the predicted disease details based on the SWRL rule specified. The motivation behind the development of this system is to spread knowledge about the children diseases and their symptoms in a very simple way using the specialized social networking website www.emama.mk.

Predicting Bullying: Maladjustment, Social Skills and Popularity

ERIC Educational Resources Information Center

Postigo, Silvia; Gonzalez, Remedios; Mateu, Carmen; Montoya, Inmaculada

2012-01-01

In order to prevent bullying, research has characterised the adolescents involved in terms of their social skills, maladjustment and popularity. However, there is a lack of knowledge concerning the relationships between these variables and how these relationships predict bullying involvement. Moreover, the literature has focused on pure bullies…

A Dual-Process Model of the Alcohol-Behavior Link for Social Drinking

ERIC Educational Resources Information Center

Moss, Antony C.; Albery, Ian P.

2009-01-01

A dual-process model of the alcohol-behavior link is presented, synthesizing 2 of the major social-cognitive approaches: expectancy and myopia theories. Substantial evidence has accrued to support both of these models, and recent neurocognitive models of the effects of alcohol on thought and behavior have provided evidence to support both as well.…

Attention Biases to Threat Link Behavioral Inhibition to Social Withdrawal over Time in Very Young Children

ERIC Educational Resources Information Center

Perez-Edgar, Koraly; Reeb-Sutherland, Bethany C.; McDermott, Jennifer Martin; White, Lauren K.; Henderson, Heather A.; Degnan, Kathryn A.; Hane, Amie A.; Pine, Daniel S.; Fox, Nathan A.

2011-01-01

Behaviorally inhibited children display a temperamental profile characterized by social withdrawal and anxious behaviors. Previous research, focused largely on adolescents, suggests that attention biases to threat may sustain high levels of behavioral inhibition (BI) over time, helping link early temperament to social outcomes. However, no prior…

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.

Social/Ethical Issues in Predictive Insider Threat Monitoring

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

Greitzer, Frank L.; Frincke, Deborah A.; Zabriskie, Mariah

2011-01-01

Combining traditionally monitored cybersecurity data with other kinds of organizational data is one option for inferring the motivations of individuals, which may in turn allow early prediction and mitigation of insider threats. While unproven, some researchers believe that this combination of data may yield better results than either cybersecurity or organizational data would in isolation. However, this nontraditional approach creates a potential conflict between goals, such as conflicts between organizational security improvements and individual privacy considerations. There are many facets to debate. Should warning signs of a potential malicious insider be addressed before a malicious event has occurred to preventmore » harm to the organization and discourage the insider from violating the organization’s rules? Would intervention violate employee trust or legal guidelines? What about the possibilities of misuse? Predictive approaches cannot be validated a priori; false accusations can affect the career of the accused; and collection/monitoring of certain types of data may affect employee morale. In this chapter, we explore some of the social and ethical issues stemming from predictive insider threat monitoring and discuss ways that a predictive modeling approach brings to the forefront social and ethical issues that should be considered and resolved by stakeholders and communities of interest.« less

CD-Based Indices for Link Prediction in Complex Network.

PubMed

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

CD-Based Indices for Link Prediction in Complex Network

PubMed Central

Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

2016-01-01

Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

Analyzing and Predicting User Participations in Online Health Communities: A Social Support Perspective

PubMed Central

Wang, Xi; Street, Nick

2017-01-01

Background Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with similar peers to seek, receive, and provide different types of social support, such as informational support, emotional support, and companionship. As active participations in an OHC are beneficial to both the OHC and its users, it is important to understand factors related to users’ participations and predict user churn for user retention efforts. Objective This study aimed to analyze OHC users’ Web-based interactions, reveal which types of social support activities are related to users’ participation, and predict whether and when a user will churn from the OHC. Methods We collected a large-scale dataset from a popular OHC for cancer survivors. We used text mining techniques to decide what kinds of social support each post contained. We illustrated how we built text classifiers for 5 different social support categories: seeking informational support (SIS), providing informational support (PIS), seeking emotional support (SES), providing emotional support (PES), and companionship (COM). We conducted survival analysis to identify types of social support related to users’ continued participation. Using supervised machine learning methods, we developed a predictive model for user churn. Results Users’ behaviors to PIS, SES, and COM had hazard ratios significantly lower than 1 (0.948, 0.972, and 0.919, respectively) and were indicative of continued participations in the OHC. The churn prediction model based on social support activities offers accurate predictions on whether and when a user will leave the OHC. Conclusions Detecting different types of social support activities via text mining contributes to better understanding and prediction of users’ participations in an OHC. The outcome of this study can help the management and design of a sustainable OHC via more proactive and effective user

Executive Function as a Mediator in the Link between Attention-Deficit/Hyperactivity Disorder and Social Problems

ERIC Educational Resources Information Center

Tseng, Wan-Ling; Gau, Susan Shur-Fen

2013-01-01

Background: Cognitive processes and mechanisms underlying the strong link between attention-deficit/hyperactivity disorder (ADHD) and social problems remain unclear. Limited knowledge also exists regarding a subgroup of youth with ADHD who do not have social problems. This study investigated the extent to which executive function (EF) mediated the…

Composite Social Network for Predicting Mobile Apps Installation

DTIC Science & Technology

2011-06-02

analysis used by social scientists such as matched sample estimation (Aral, Muchnik, and Sundararajan 2009) are only for identifying network effects and...ar X iv :1 10 6. 03 59 v1 [ cs .S I] 2 J un 2 01 1 Composite Social Network for Predicting Mobile Apps Installation Wei Pan and Nadav Aharony...and Alex (Sandy) Pentland MIT Media Laboratory 20 Ames Street Cambridge, Massachusetts 02139 Abstract We have carefully instrumented a large portion of

Links Between Remembered Childhood Emotion Socialization and Adult Adjustment: Similarities and Differences Between European American and African American Women

PubMed Central

Leerkes, Esther M.; Supple, Andrew J.; Su, Jinni; Cavanaugh, Alyson M.

2017-01-01

The purpose of this paper was to examine whether recollections of mothers’ emotion socialization practices during childhood are linked to adult emotional well-being as indexed by depression, trait anger, and cardiac vagal tone, and whether these effects vary for African American and European American women. Participants included 251 women (128 European American; 123 African American) who ranged in age from 18 to 44 years (M = 25 years). Multigroup confirmatory factor analyses indicated strong measurement and factor invariance across African American and European American participants. Remembered non-supportive emotion socialization was linked with elevated depressive symptoms for European American women, but not African American women and with elevated trait anger for both groups. Remembered supportive emotion socialization was linked with higher resting vagal tone for both groups. The results provide some support for the view that non-supportive emotion socialization may be more detrimental for European Americans than African Americans. PMID:29527083

Perceived social support interacts with prenatal depression to predict birth outcomes.

PubMed

Nylen, Kimberly J; O'Hara, Michael W; Engeldinger, Jane

2013-08-01

Prenatal depression has been linked to adverse reproductive outcomes including preterm labor and delivery, and low birth weight. Social support also has been linked to birth outcomes, and may buffer infants from the adverse impact of maternal depression. In this prospective study, 235 pregnant women completed questionnaires about depression and social support. Clinical interviews were administered to assess for DSM-IV axis I disorders. Following delivery, birth outcomes were obtained from medical records. Babies of depressed mothers weighed less, were born earlier and had lower Apgar scores than babies of nondepressed mothers. Depressed women had smaller social support networks and were less satisfied with support from social networks. We found no direct associations between perceived social support and birth weight. However, depressed women who rated their partners as less supportive had babies who were born earlier and had lower Apgar scores than depressed mothers with higher perceived partner support. Women's perception of partner support appears to buffer infants of depressed mothers from potential adverse outcomes. These results are notable in light of the low-risk nature of our sample and point to the need for continued depression screening in pregnant women and a broader view of risk for adverse birth outcomes. The results also suggest a possible means of intervention that may ultimately lead to reductions in adverse birth outcomes.

Hyperscanning: simultaneous fMRI during linked social interactions.

PubMed

Montague, P Read; Berns, Gregory S; Cohen, Jonathan D; McClure, Samuel M; Pagnoni, Giuseppe; Dhamala, Mukesh; Wiest, Michael C; Karpov, Igor; King, Richard D; Apple, Nathan; Fisher, Ronald E

2002-08-01

"Plain question and plain answer make the shortest road out of most perplexities." Mark Twain-Life on the Mississippi. A new methodology for the measurement of the neural substrates of human social interaction is described. This technology, termed "Hyperscan," embodies both the hardware and the software necessary to link magnetic resonance scanners through the internet. Hyperscanning allows for the performance of human behavioral experiments in which participants can interact with each other while functional MRI is acquired in synchrony with the behavioral interactions. Data are presented from a simple game of deception between pairs of subjects. Because people may interact both asymmetrically and asynchronously, both the design and the analysis must accommodate this added complexity. Several potential approaches are described.

Social-Perspective Coordination and Gifted Adolescents' Friendship Quality

ERIC Educational Resources Information Center

Masden, Catherine A.; Leung, Olivia N.; Shore, Bruce M.; Schneider, Barry H.; Udvari, Stephen J.

2015-01-01

This research examined links among academic ability, social-perspective coordination, and friendship quality, within the context of gifted adolescents' friendships. The sample consisted of 120 early adolescents (59 girls, 61 boys), 81 of whom were identified as gifted. Academic ability, sex, and grade significantly predicted social-perspective…

Does workplace social capital protect against long-term sickness absence? Linking workplace aggregated social capital to sickness absence registry data

PubMed Central

Hansen, Anne-Sophie K.; Madsen, Ida E. H.; Thorsen, Sannie Vester; Melkevik, Ole; Bjørner, Jakob Bue; Andersen, Ingelise; Rugulies, Reiner

2017-01-01

Aims: Most previous prospective studies have examined workplace social capital as a resource of the individual. However, literature suggests that social capital is a collective good. In the present study we examined whether a high level of workplace aggregated social capital (WASC) predicts a decreased risk of individual-level long-term sickness absence (LTSA) in Danish private sector employees. Methods: A sample of 2043 employees (aged 18–64 years, 38.5% women) from 260 Danish private-sector companies filled in a questionnaire on workplace social capital and covariates. WASC was calculated by assigning the company-averaged social capital score to all employees of each company. We derived LTSA, defined as sickness absence of more than three weeks, from a national register. We examined if WASC predicted employee LTSA using multilevel survival analyses, while excluding participants with LTSA in the three months preceding baseline. Results: We found no statistically significant association in any of the analyses. The hazard ratio for LTSA in the fully adjusted model was 0.93 (95% CI 0.77–1.13) per one standard deviation increase in WASC. When using WASC as a categorical exposure we found a statistically non-significant tendency towards a decreased risk of LTSA in employees with medium WASC (fully adjusted model: HR 0.78 (95% CI 0.48–1.27)). Post hoc analyses with workplace social capital as a resource of the individual showed similar results. Conclusions: WASC did not predict LTSA in this sample of Danish private-sector employees. PMID:28784025

Social networks and links to isolation and loneliness among elderly HCBS clients.

PubMed

Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita

2016-01-01

The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.

A review of influenza detection and prediction through social networking sites.

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases seven to ten days faster than government agencies such as Center of Disease Control and Prevention (CDC). CDC uses the Illness-Like Influenza Surveillance Network (ILINet), which is a program used to monitor Influenza-Like Illness (ILI) sent by thousands of health care providers in order to detect influenza outbreaks. It is a reliable tool, however, it is slow and expensive. For that reason, many studies aim to develop methods that do real time analysis to track ILI using social networking sites. Social media data such as Twitter can be used to predict the spread of flu in the population and can help in getting early warnings. Today, social networking sites (SNS) are used widely by many people to share thoughts and even health status. Therefore, SNS provides an efficient resource for disease surveillance and a good way to communicate to prevent disease outbreaks. The goal of this study is to review existing alternative solutions that track flu outbreak in real time using social networking sites and web blogs. Many studies have shown that social networking sites can be used to conduct real time analysis for better predictions.

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial. PMID:23563395

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

PubMed

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

Predicting Adolescents' Bullying Participation from Developmental Trajectories of Social Status and Behavior.

PubMed

Pouwels, J Loes; Salmivalli, Christina; Saarento, Silja; van den Berg, Yvonne H M; Lansu, Tessa A M; Cillessen, Antonius H N

2017-03-28

The aim of this study was to determine how trajectory clusters of social status (social preference and perceived popularity) and behavior (direct aggression and prosocial behavior) from age 9 to age 14 predicted adolescents' bullying participant roles at age 16 and 17 (n = 266). Clusters were identified with multivariate growth mixture modeling (GMM). The findings showed that participants' developmental trajectories of social status and social behavior across childhood and early adolescence predicted their bullying participant role involvement in adolescence. Practical implications and suggestions for further research are discussed. © 2017 The Authors. Child Development published by Wiley Periodicals, Inc. on behalf of Society for Research in Child Development.

Using LinkedIn in the Marketing Classroom: Exploratory Insights and Recommendations for Teaching Social Media/Networking

ERIC Educational Resources Information Center

McCorkle, Denny E.; McCorkle, Yuhua Li

2012-01-01

With the rapid growth of social networking and media comes their consideration for use in the marketing classroom. Social networking skills are becoming essential for personal branding (e.g., networking, self-marketing) and corporate/product branding (e.g., marketing communication). This paper addresses the use of LinkedIn (i.e., an online…

Predicting vigorous physical activity using social cognitive theory.

PubMed

Petosa, R Lingyak; Suminski, Rick; Hortz, Brian

2003-01-01

To test Social Cognitive Theory (SCT) in predicting future vigorous physical activity among college students. College students (n=350) completed a set of instruments measuring SCT constructs. Their vigorous physical activity was tracked for 4 weeks. Exercise role identity, self-regulation, outcome expectancy value, social support, self-efficacy, and positive exercise experience accounted for 27% of the variance in days of vigorous physical activity. The results supported the use of SCT in understanding factors associated with vigorous physical activity rates among college students.

Predicting Individual Characteristics from Digital Traces on Social Media: A Meta-Analysis.

PubMed

Settanni, Michele; Azucar, Danny; Marengo, Davide

2018-04-01

The increasing utilization of social media provides a vast and new source of user-generated ecological data (digital traces), which can be automatically collected for research purposes. The availability of these data sets, combined with the convergence between social and computer sciences, has led researchers to develop automated methods to extract digital traces from social media and use them to predict individual psychological characteristics and behaviors. In this article, we reviewed the literature on this topic and conducted a series of meta-analyses to determine the strength of associations between digital traces and specific individual characteristics; personality, psychological well-being, and intelligence. Potential moderator effects were analyzed with respect to type of social media platform, type of digital traces examined, and study quality. Our findings indicate that digital traces from social media can be studied to assess and predict theoretically distant psychosocial characteristics with remarkable accuracy. Analysis of moderators indicated that the collection of specific types of information (i.e., user demographics), and the inclusion of different types of digital traces, could help improve the accuracy of predictions.

Social isolation induces autophagy in the mouse mammary gland: link to increased mammary cancer risk

PubMed Central

Sumis, Allison; Cook, Katherine L; Andrade, Fabia O; Hu, Rong; Kidney, Emma; Zhang, Xiyuan; Kim, Dominic; Carney, Elissa; Nguyen, Nguyen; Yu, Wei; Bouker, Kerrie B; Cruz, Idalia; Clarke, Robert; Hilakivi-Clarke, Leena

2018-01-01

Social isolation is a strong predictor of early all-cause mortality and consistently increases breast cancer risk in both women and animal models. Because social isolation increases body weight, we compared its effects to those caused by a consumption of obesity-inducing diet (OID) in C57BL/6 mice. Social isolation and OID impaired insulin and glucose sensitivity. In socially isolated, OID-fed mice (I-OID), insulin resistance was linked to reduced Pparg expression and increased neuropeptide Y levels, but in group-housed OID fed mice (G-OID), it was linked to increased leptin and reduced adiponectin levels, indicating that the pathways leading to insulin resistance are different. Carcinogen-induced mammary tumorigenesis was significantly higher in I-OID mice than in the other groups, but cancer risk was also increased in socially isolated, control diet-fed mice (I-C) and G-OID mice compared with that in controls. Unfolded protein response (UPR) signaling (GRP78; IRE1) was upregulated in the mammary glands of OID-fed mice, but not in control diet-fed, socially isolated I-C mice. In contrast, expression of BECLIN1, ATG7 and LC3II were increased, and p62 was downregulated by social isolation, indicating increased autophagy. In the mammary glands of socially isolated mice, but not in G-OID mice, mRNA expressions of p53 and the p53-regulated autophagy inducer Dram1 were upregulated, and nuclear p53 staining was strong. Our findings further indicated that autophagy and tumorigenesis were not increased in Atg7+/− mice kept in social isolation and fed OID. Thus, social isolation may increase breast cancer risk by inducing autophagy, independent of changes in body weight. PMID:27550962

Social isolation induces autophagy in the mouse mammary gland: link to increased mammary cancer risk.

PubMed

Sumis, Allison; Cook, Katherine L; Andrade, Fabia O; Hu, Rong; Kidney, Emma; Zhang, Xiyuan; Kim, Dominic; Carney, Elissa; Nguyen, Nguyen; Yu, Wei; Bouker, Kerrie B; Cruz, Idalia; Clarke, Robert; Hilakivi-Clarke, Leena

2016-10-01

Social isolation is a strong predictor of early all-cause mortality and consistently increases breast cancer risk in both women and animal models. Because social isolation increases body weight, we compared its effects to those caused by a consumption of obesity-inducing diet (OID) in C57BL/6 mice. Social isolation and OID impaired insulin and glucose sensitivity. In socially isolated, OID-fed mice (I-OID), insulin resistance was linked to reduced Pparg expression and increased neuropeptide Y levels, but in group-housed OID fed mice (G-OID), it was linked to increased leptin and reduced adiponectin levels, indicating that the pathways leading to insulin resistance are different. Carcinogen-induced mammary tumorigenesis was significantly higher in I-OID mice than in the other groups, but cancer risk was also increased in socially isolated, control diet-fed mice (I-C) and G-OID mice compared with that in controls. Unfolded protein response (UPR) signaling (GRP78; IRE1) was upregulated in the mammary glands of OID-fed mice, but not in control diet-fed, socially isolated I-C mice. In contrast, expression of BECLIN1, ATG7 and LC3II were increased, and p62 was downregulated by social isolation, indicating increased autophagy. In the mammary glands of socially isolated mice, but not in G-OID mice, mRNA expressions of p53 and the p53-regulated autophagy inducer Dram1 were upregulated, and nuclear p53 staining was strong. Our findings further indicated that autophagy and tumorigenesis were not increased in Atg7(+/-) mice kept in social isolation and fed OID. Thus, social isolation may increase breast cancer risk by inducing autophagy, independent of changes in body weight. © 2016 Society for Endocrinology.

Self-regulating the effortful "social dos".

PubMed

Cortes, Kassandra; Kammrath, Lara K; Scholer, Abigail A; Peetz, Johanna

2014-03-01

In the current research, we explored differences in the self-regulation of the personal dos (i.e., engaging in active and effortful behaviors that benefit the self) and in the self-regulation of the social dos (engaging in those same effortful behaviors to benefit someone else). In 6 studies, we examined whether the same trait self-control abilities that predict task persistence on personal dos would also predict task persistence on social dos. That is, would the same behavior, such as persisting through a tedious and attentionally demanding task, show different associations with trait self-control when it is framed as benefitting the self versus someone else? In Studies 1-3, we directly compared the personal and social dos and found that trait self-control predicted self-reported and behavioral personal dos but not social dos, even when the behaviors were identical and when the incentives were matched. Instead, trait agreeableness--a trait linked to successful self-regulation within the social domain--predicted the social dos. Trait self-control did not predict the social dos even when task difficulty increased (Study 4), but it did predict the social don'ts, consistent with past research (Studies 5-6). The current studies provide support for the importance of distinguishing different domains of self-regulated behaviors and suggest that social dos can be successfully performed through routes other than traditional self-control abilities. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

The SAIL databank: linking multiple health and social care datasets

PubMed Central

2009-01-01

Background Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Methods Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. Results The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were < 0.2%. A range of techniques for matching datasets to the NHSAR were applied and the optimum technique resulted in sensitivity values of: 99.9% for a GP dataset from primary care, 99.3% for a PEDW dataset from secondary care and 95.2% for the PARIS database from social care. Conclusion With the infrastructure that has been put in place, the

The SAIL databank: linking multiple health and social care datasets.

PubMed

Lyons, Ronan A; Jones, Kerina H; John, Gareth; Brooks, Caroline J; Verplancke, Jean-Philippe; Ford, David V; Brown, Ginevra; Leake, Ken

2009-01-16

Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were < 0.2%. A range of techniques for matching datasets to the NHSAR were applied and the optimum technique resulted in sensitivity values of: 99.9% for a GP dataset from primary care, 99.3% for a PEDW dataset from secondary care and 95.2% for the PARIS database from social care. With the infrastructure that has been put in place, the reliable matching process that has been

Neighborhood linking social capital as a predictor of psychiatric medication prescription in the elderly: a Swedish national cohort study.

PubMed

Sundquist, Jan; Hamano, Tsuyoshi; Li, Xinjun; Kawakami, Naomi; Shiwaku, Kuninori; Sundquist, Kristina

2014-08-01

Little is known about the association between neighborhood linking social capital and psychiatric medication in the elderly. The present study analyzes whether there is an association between linking social capital (a theoretical concept describing the amount of trust between individuals and societal institutions) and prescription of antipsychotics, anxiolytics, hypnotics/sedatives, antidepressants, or anti-dementia drugs. The entire Swedish population aged 65+, a total of 1,292,816 individuals, were followed from 1 July 2005 until first prescription of psychiatric medication, death, emigration, or the end of the study on 31 December 2010. Small geographic units were used to define neighborhoods. The definition of linking social capital was based on mean voting participation in each neighborhood unit, categorized in three groups. Multilevel logistic regression was used to estimate odds ratios (ORs) and between-neighborhood variance in three different models. There was an inverse association between the level of linking social capital and prescription of psychiatric medications (except for anti-dementia drugs). The associations decreased, but remained significant, after accounting for age, sex, family income, marital status, country of birth, and education level (except for antidepressants). The OR for prescription of antipsychotics in the crude model was 1.65 (95% CI 1.53-1.78) and decreased, but remained significant (OR = 1.26; 95% CI 1.17-1.35), after adjustment for the individual-level sociodemographic variables. Decision-makers should take into account the potentially negative effect of linking social capital on psychiatric disorders when planning sites of primary care centers and psychiatric clinics, as well as other kinds of community support for elderly patients with such disorders. Copyright © 2014 Elsevier Ltd. All rights reserved.

Positive affect predicts avoidance goals in social interaction anxiety: testing a hierarchical model of social goals.

PubMed

Trew, Jennifer L; Alden, Lynn E

2012-01-01

Models of self-regulation suggest that social goals may contribute to interpersonal and affective difficulties, yet little research has addressed this issue in the context of social anxiety. The present studies evaluated a hierarchical model of approach and avoidance in the context of social interaction anxiety, with affect as a mediating factor in the relationship between motivational tendencies and social goals. This model was refined in one undergraduate sample (N = 186) and cross-validated in a second sample (N = 195). The findings support hierarchical relationships between motivational tendencies, social interaction anxiety, affect, and social goals, with higher positive affect predicting fewer avoidance goals in both samples. Implications for the treatment of social interaction anxiety are discussed.

SOCIAL RELATIONSHIPS AND SLEEP QUALITY

PubMed Central

Kent, Robert G.; Uchino, Bert N.; Cribbet, Matthew R.; Bowen, Kimberly; Smith, Timothy W.

2015-01-01

Background The quality of social relationships and social support appears to be associated with physical health outcomes and sleep quality. Almost all previous research in this area focuses on positive aspects of relationships. Purpose The present study thus intended to examine the links between supportive, aversive, ambivalent, and indifferent network ties and sleep quality. Methods Relationship data, PSQI-assessed sleep quality, and depression were examined in 175 middle-aged and older adults. Results Consistent with hypotheses, supportive ties were positively related to sleep quality, while aversive ties predicted worse sleep quality; associations that were primarily seen for close relationships. Ambivalent and indifferent ties were not significant predictors of sleep quality. Importantly, depression was found to mediate the link between relationship quality and sleep quality. Conclusions These data suggest the more specific types of social relationships that may be linked to poor sleep quality, and that depression appears to underlie these associations. PMID:25976874

Analyzing and Predicting User Participations in Online Health Communities: A Social Support Perspective.

PubMed

Wang, Xi; Zhao, Kang; Street, Nick

2017-04-24

Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with similar peers to seek, receive, and provide different types of social support, such as informational support, emotional support, and companionship. As active participations in an OHC are beneficial to both the OHC and its users, it is important to understand factors related to users' participations and predict user churn for user retention efforts. This study aimed to analyze OHC users' Web-based interactions, reveal which types of social support activities are related to users' participation, and predict whether and when a user will churn from the OHC. We collected a large-scale dataset from a popular OHC for cancer survivors. We used text mining techniques to decide what kinds of social support each post contained. We illustrated how we built text classifiers for 5 different social support categories: seeking informational support (SIS), providing informational support (PIS), seeking emotional support (SES), providing emotional support (PES), and companionship (COM). We conducted survival analysis to identify types of social support related to users' continued participation. Using supervised machine learning methods, we developed a predictive model for user churn. Users' behaviors to PIS, SES, and COM had hazard ratios significantly lower than 1 (0.948, 0.972, and 0.919, respectively) and were indicative of continued participations in the OHC. The churn prediction model based on social support activities offers accurate predictions on whether and when a user will leave the OHC. Detecting different types of social support activities via text mining contributes to better understanding and prediction of users' participations in an OHC. The outcome of this study can help the management and design of a sustainable OHC via more proactive and effective user retention strategies. ©Xi Wang, Kang Zhao, Nick Street. Originally

A real-time method to predict social media popularity

NASA Astrophysics Data System (ADS)

Chen, Xiao; Lu, Zhe-Ming

How to predict the future popularity of a message or video on online social media (OSM) has long been an attractive problem for researchers. Although many difficulties are still ahead, recent studies suggest that temporal and topological features of early adopters generally play a very important role. However, with the increase of the adopters, the feature space will grow explosively. How to select the most effective features is still an open issue. In this work, we investigate several feature extraction methods over the Twitter platform and find that most predictive power concentrates on the second half of the propagation period, and that not only a model trained on one platform generalizes well to others as previous works observed, but also a model trained on one dataset performs well on predicting the popularity for other datasets with different number of observed early adopters. According to these findings, at least for the best features by far, the data used to extract features can be halved without loss of evident accuracy and we provide a way to roughly predict the growth trend of a social-media item in real-time.

Extended resource allocation index for link prediction of complex network

NASA Astrophysics Data System (ADS)

Liu, Shuxin; Ji, Xinsheng; Liu, Caixia; Bai, Yi

2017-08-01

Recently, a number of similarity-based methods have been proposed to predict the missing links in complex network. Among these indices, the resource allocation index performs very well with lower time complexity. However, it ignores potential resources transferred by local paths between two endpoints. Motivated by the resource exchange taking places between endpoints, an extended resource allocation index is proposed. Empirical study on twelve real networks and three synthetic dynamic networks has shown that the index we proposed can achieve a good performance, compared with eight mainstream baselines.

The Inverse Contagion Problem (ICP) vs.. Predicting site contagion in real time, when network links are not observable

NASA Astrophysics Data System (ADS)

Mushkin, I.; Solomon, S.

2017-10-01

We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires "only" the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the "false link difficulty". By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the "false link difficulty" of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it

Radio link design framework for WSN deployment and performance prediction

NASA Astrophysics Data System (ADS)

Saponara, Sergio; Giannetti, Filippo

2017-05-01

For an easy implementation of wireless sensor and actuator networks (WSAN), the state-of-the-art is offering single-chip solutions embedding in the same device a microcontroller core with a wireless transceiver. These internet-on-chip devices support different protocols (Bluetooth, ZigBee, Bluetooth Low Energy, sub- GHz links), from about 300 MHz to 6 GHz, with max. sustained bit-rates from 250 kb/s (sub-GHz links) to 4 Mb/s (Wi-Fi), and different trade-offs between RX sensitivity (from -74 to -100 dBm), RX noise figure (few dB to 10 dB), maximum TX power (from 0 to 22 dBm), link distances, power consumption levels (from few mW to several hundreds of mW). One limit for their successful application is the missing of an easy-to-use modeling and simulation environment to plan their deployment. The need is to predict, before installing a network, at which distances the sensors can be deployed, the real achievable bit-rate, communication latency, outage probability, power consumption, battery duration. To this aim, this paper presents the H2AWKS (Harsh environment and Hardware Aware Wireless linK Simulator) simulator, which allows the planning of a WSAN taking into account environment constraints and hardware parameters. Applications of H2AWKS to real WSAN case studies prove that it is an easy to use simulation environment, which allows design exploration of the system performance of a WSAN as a function of the operating environment and of the hardware parameters of the used devices.

Domains of Social Support That Predict Bereavement Distress Following Homicide Loss.

PubMed

Bottomley, Jamison S; Burke, Laurie A; Neimeyer, Robert A

2017-05-01

Psychological adaptation following homicide loss can prove more challenging for grievers than other types of losses. Although social support can be beneficial in bereavement, research is mixed in terms of identifying whether it serves as a buffer to distress following traumatic loss. In particular, studies have not parsed out specific domains of social support that best predict positive bereavement outcomes. Recruiting a sample of 47 African Americans bereaved by homicide, we examined six types of social support along with the griever's perceived need for or satisfaction with each and analyzed them in relation to depression, anxiety, complicated grief, and posttraumatic stress disorder outcomes. Results of multivariate analyses revealed that the griever's level of satisfaction with physical assistance at the initial assessment best predicted lower levels of depression, anxiety, and posttraumatic stress disorder levels 6 months later, while less need for physical assistance predicted lower complicated grief at follow-up. Clinical implications and suggestions for future research are discussed.

Ambivalence About Interpersonal Problems and Traits Predicts Cross-Situational Variability of Social Behavior.

PubMed

Erickson, Thane M; Newman, Michelle G; Peterson, Jessica; Scarsella, Gina

2015-08-01

Multiple theoretical perspectives suggest that maladjusted personality is characterized by not only distress, but also opposing or "ambivalent" self-perceptions and behavioral lability across social interactions. However, the degree to which ambivalence about oneself predicts cross-situational variability in social behavior has not been examined empirically. Using the interpersonal circumplex (IPC) as a nomological framework, the present study investigated the extent to which endorsing opposing or "ambivalent" tendencies on IPC measures predicted variability in social behavior across a range of hypothetical interpersonal scenarios (Part 1; N = 288) and naturalistic social interactions (Part 2; N = 192). Ambivalent responding for interpersonal problems and traits was associated with measures of distress, maladaptive interpersonal tendencies, and greater variability of social behavior across both hypothetical and daily social interactions, though more consistently for interpersonal problems. More conservative tests suggested that ambivalence predicted some indexes of behavioral variability even when accounting for mean levels and squared means of social behaviors, vector length, gender, and depressive symptoms. Results suggest that processes theorized as typifying personality disorder may apply more broadly to personality maladjustment occurring outside of clinical samples. © 2014 Wiley Periodicals, Inc.

Talking Less during Social Interactions Predicts Enjoyment: A Mobile Sensing Pilot Study

PubMed Central

Sandstrom, Gillian M.; Tseng, Vincent Wen-Sheng; Costa, Jean; Okeke, Fabian; Choudhury, Tanzeem; Dunn, Elizabeth W.

2016-01-01

Can we predict which conversations are enjoyable without hearing the words that are spoken? A total of 36 participants used a mobile app, My Social Ties, which collected data about 473 conversations that the participants engaged in as they went about their daily lives. We tested whether conversational properties (conversation length, rate of turn taking, proportion of speaking time) and acoustical properties (volume, pitch) could predict enjoyment of a conversation. Surprisingly, people enjoyed their conversations more when they spoke a smaller proportion of the time. This pilot study demonstrates how conversational properties of social interactions can predict psychologically meaningful outcomes, such as how much a person enjoys the conversation. It also illustrates how mobile phones can provide a window into everyday social experiences and well-being. PMID:27438475

Social Relationships, Inflammation, and Cancer Survival.

PubMed

Boen, Courtney E; Barrow, David A; Bensen, Jeannette T; Farnan, Laura; Gerstel, Adrian; Hendrix, Laura H; Yang, Yang Claire

2018-05-01

Background: Social stressors, such as social relationship deficits, have been increasingly linked to chronic disease outcomes, including cancer. However, critical gaps exist in our understanding of the nature and strength of such links, as well as the underlying biological mechanisms relating social relationships to cancer progression and survival. Methods: Utilizing novel questionnaire and biomarker data from the UNC Health Registry/Cancer Survivorship Cohort, this study examines the associations between diverse measures of social support and mortality risk among individuals with cancer ( N = 1,004). We further assess the role of multiple serum markers of inflammation, including high-sensitivity C-reactive protein (CRP), IL6, TNFα, and VEGF, as potential mediators in the social relationship-cancer link. Results: The findings revealed that one's appraisal of their social support was associated with cancer mortality, such that individuals reporting higher levels of social support satisfaction had lower mortality risk than individuals reporting lower levels of satisfaction. The amount of support received, on the other hand, was not predictive of cancer survival. We further found evidence that inflammatory processes may undergird the link between social support satisfaction and mortality among individuals with cancer, with individuals reporting higher levels of social support satisfaction having lower levels of CRP, IL6, and TNFα. Conclusions: These results provide new knowledge of the biosocial processes producing population disparities in cancer outcomes. Impact: Our study offers new insights for intervention efforts aimed at promoting social connectedness as a means for improving cancer survival. Cancer Epidemiol Biomarkers Prev; 27(5); 541-9. ©2018 AACR . ©2018 American Association for Cancer Research.

Personality moderates the links of social identity with work motivation and job searching.

PubMed

Baay, Pieter E; van Aken, Marcel A G; van der Lippe, Tanja; de Ridder, Denise T D

2014-01-01

Work motivation is critical for successful school-to-work transitions, but little is known about its determinants among labor market entrants. Applying a social identity framework, we examined whether work motivation and job searching are social-contextually determined. We expected that some job seekers are more sensitive to contextual influence, depending on their personality. Mediation analyses on 591 Dutch vocational training students indicate that the perception of more positive work norms in someone's social context was related to higher levels of intrinsic motivation, which in turn predicted higher preparatory job search behavior and job search intentions. Multi-group analysis shows that perceived work norms more strongly predict work motivation among overcontrollers compared to resilients and undercontrollers. In conclusion, work motivation and job searching appear contextually determined: especially among those sensitive to contextual influence, people seem to work when they believe that is what people like them do.

Trait and Social Influences in the Links among Adolescent Attachment, Depressive Symptoms, and Coping

ERIC Educational Resources Information Center

Merlo, Lisa J.; Lakey, Brian

2007-01-01

Attachment insecurity and maladaptive coping are associated with depression in adolescence; however, it is unclear whether these links primarily reflect stable individual differences among teens (trait influences), experiential differences in their interactions with relationship partners (social influences) or both. In this study, teens (ages…

Parental ethnic-racial socialization and social attitudes among ethnic-racial minority and White American emerging adults.

PubMed

Tran, Alisia G T T; Mintert, Jeffrey S; Jew, Gilbert B

2017-01-01

This article utilizes moderated mediation analyses to explore whether the relations between parental ethnic-racial socialization (PERS) dimensions and social attitudes differ across ethnic-racial minority (n = 128) and White (n = 131) college-going emerging adults. We examined social dominance orientation (SDO) as an index of antiegalitarian intergroup attitudes and attitudes toward interpersonal harmony as an index of interpersonal attitudes. We tested whether there were ethnic-racial variations in mediation models in which each type of PERS dimension was expected to be linked to greater antiegalitarian attitudes (greater SDO), which, in turn, was predicted to be associated with less prosocial attitudes (lower harmony enhancement). Results indicated that more frequent cultural socialization and preparation for bias were linked to greater SDO for the White sample, but not for the ethnic-minority sample. Moderation results were nonsignificant for promotion of mistrust, with results indicating a positive link to SDO, regardless of racial-ethnic status. Moderated mediation analyses further revealed indirect effects of cultural socialization and preparation for bias on interpersonal attitudes through SDO for the White sample, but not for the ethnic-minority sample. Specifically, greater cultural socialization and preparation for bias each were linked to greater SDO, which, in turn, was associated with less positive perceptions of the value of maintaining interpersonal harmony for White respondents. Practical applications, including social justice implications, of the results and possibilities for future research are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Linking communities to formal health care providers through village health teams in rural Uganda: lessons from linking social capital.

PubMed

Musinguzi, Laban Kashaija; Turinawe, Emmanueil Benon; Rwemisisi, Jude T; de Vries, Daniel H; Mafigiri, David K; Muhangi, Denis; de Groot, Marije; Katamba, Achilles; Pool, Robert

2017-01-11

Community-based programmes, particularly community health workers (CHWs), have been portrayed as a cost-effective alternative to the shortage of health workers in low-income countries. Usually, literature emphasises how easily CHWs link and connect communities to formal health care services. There is little evidence in Uganda to support or dispute such claims. Drawing from linking social capital framework, this paper examines the claim that village health teams (VHTs), as an example of CHWs, link and connect communities with formal health care services. Data were collected through ethnographic fieldwork undertaken as part of a larger research program in Luwero District, Uganda, between 2012 and 2014. The main methods of data collection were participant observation in events organised by VHTs. In addition, a total of 91 in-depth interviews and 42 focus group discussions (FGD) were conducted with adult community members as part of the larger project. After preliminary analysis of the data, we conducted an additional six in-depth interviews and three FGD with VHTs and four FGD with community members on the role of VHTs. Key informant interviews were conducted with local government staff, health workers, local leaders, and NGO staff with health programs in Luwero. Thematic analysis was used during data analysis. The ability of VHTs to link communities with formal health care was affected by the stakeholders' perception of their roles. Community members perceive VHTs as working for and under instructions of "others", which makes them powerless in the formal health care system. One of the challenges associated with VHTs' linking roles is support from the government and formal health care providers. Formal health care providers perceived VHTs as interested in special recognition for their services yet they are not "experts". For some health workers, the introduction of VHTs is seen as a ploy by the government to control people and hide its inability to provide health

Scratch that itch: revisiting links between self-directed behaviour and parasitological, social and environmental factors in a free-ranging primate

PubMed Central

Romano, Valéria; MacIntosh, Andrew J. J.

2016-01-01

Different hypotheses explain variation in the occurrence of self-directed behaviour such as scratching and self-grooming: a parasite hypothesis linked with ectoparasite load, an environmental hypothesis linked with seasonal conditions and a social hypothesis linked with social factors. These hypotheses are not mutually exclusive but are often considered separately. Here, we revisited these hypotheses together in female Japanese macaques (Macaca fuscata fuscata) of Kōjima islet, Japan. We input occurrences of scratching and self-grooming during focal observations in models combining parasitological (lice load), social (dominance rank, social grooming, aggression received and proximity), and environmental (rainfall, temperature and season) variables. Using an information-theory approach, we simultaneously compared the explanatory value of models against each other using variation in Akaike's information criterion and Akaike's weights. We found that evidence for models with lice load, with or without environmental–social parameters, was stronger than that for other models. In these models, scratching was positively associated with lice load and social grooming whereas self-grooming was negatively associated with lice load and positively associated with social grooming, dominance rank and number of female neighbours. This study indicates that the study animals scratch primarily because of an immune/stimulus itch, possibly triggered by ectoparasite bites/movements. It also confirms that self-grooming could act as a displacement activity in the case of social uncertainty. We advocate that biological hypotheses be more broadly considered even when investigating social processes, as one does not exclude the other. PMID:28018646

MSD-MAP: A Network-Based Systems Biology Platform for Predicting Disease-Metabolite Links.

PubMed

Wathieu, Henri; Issa, Naiem T; Mohandoss, Manisha; Byers, Stephen W; Dakshanamurthy, Sivanesan

2017-01-01

Cancer-associated metabolites result from cell-wide mechanisms of dysregulation. The field of metabolomics has sought to identify these aberrant metabolites as disease biomarkers, clues to understanding disease mechanisms, or even as therapeutic agents. This study was undertaken to reliably predict metabolites associated with colorectal, esophageal, and prostate cancers. Metabolite and disease biological action networks were compared in a computational platform called MSD-MAP (Multi Scale Disease-Metabolite Association Platform). Using differential gene expression analysis with patient-based RNAseq data from The Cancer Genome Atlas, genes up- or down-regulated in cancer compared to normal tissue were identified. Relational databases were used to map biological entities including pathways, functions, and interacting proteins, to those differential disease genes. Similar relational maps were built for metabolites, stemming from known and in silico predicted metabolite-protein associations. The hypergeometric test was used to find statistically significant relationships between disease and metabolite biological signatures at each tier, and metabolites were assessed for multi-scale association with each cancer. Metabolite networks were also directly associated with various other diseases using a disease functional perturbation database. Our platform recapitulated metabolite-disease links that have been empirically verified in the scientific literature, with network-based mapping of jointly-associated biological activity also matching known disease mechanisms. This was true for colorectal, esophageal, and prostate cancers, using metabolite action networks stemming from both predicted and known functional protein associations. By employing systems biology concepts, MSD-MAP reliably predicted known cancermetabolite links, and may serve as a predictive tool to streamline conventional metabolomic profiling methodologies. Copyright© Bentham Science Publishers; For any

Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services.

PubMed

Kasthurirathne, Suranga N; Vest, Joshua R; Menachemi, Nir; Halverson, Paul K; Grannis, Shaun J

2018-01-01

A growing variety of diverse data sources is emerging to better inform health care delivery and health outcomes. We sought to evaluate the capacity for clinical, socioeconomic, and public health data sources to predict the need for various social service referrals among patients at a safety-net hospital. We integrated patient clinical data and community-level data representing patients' social determinants of health (SDH) obtained from multiple sources to build random forest decision models to predict the need for any, mental health, dietitian, social work, or other SDH service referrals. To assess the impact of SDH on improving performance, we built separate decision models using clinical and SDH determinants and clinical data only. Decision models predicting the need for any, mental health, and dietitian referrals yielded sensitivity, specificity, and accuracy measures ranging between 60% and 75%. Specificity and accuracy scores for social work and other SDH services ranged between 67% and 77%, while sensitivity scores were between 50% and 63%. Area under the receiver operating characteristic curve values for the decision models ranged between 70% and 78%. Models for predicting the need for any services reported positive predictive values between 65% and 73%. Positive predictive values for predicting individual outcomes were below 40%. The need for various social service referrals can be predicted with considerable accuracy using a wide range of readily available clinical and community data that measure socioeconomic and public health conditions. While the use of SDH did not result in significant performance improvements, our approach represents a novel and important application of risk predictive modeling. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Stock price change rate prediction by utilizing social network activities.

PubMed

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

PubMed Central

Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

Caring for the Unseen: Using Linking Social Capital to Improve Healthcare Access to Irregular Migrants in Spain

PubMed Central

2016-01-01

Abstract Purpose To describe a novel strategy using linking social capital to provide healthcare access to irregular migrants with low literacy, low numeracy, and limited cultural assimilation in a European metropolitan area. Organizing Construct Public data show numerous shortcomings in meeting the healthcare needs of refugees and irregular migrants surging into Europe. Many irregular migrants living in European communities are unable to access information, care, or services due to lack of social capital. An overview of the problem and traditional charity strategies, including their barriers, are briefly described. A novel strategy using linking social capital to improve healthcare access of irregular migrants is explored and described. Information regarding the impact of this approach on the target population is provided. The discussion of nursing's role in employing linking social capital to care for the vulnerable is presented. Conclusions Immigration and refugee data show that issues related to migration will continue. The novel strategy presented can be implemented by nurses with limited financial and physical resources in small community settings frequented by irregular migrants to improve health care. Clinical Relevance The health and well‐being of irregular migrants has an impact on community health. Nurses must be aware of and consider implementing novel strategies to ensure that all community members’ healthcare needs, which are a basic human right, are addressed. PMID:27355488

How Different Guilt Feelings Can Affect Social Competence Development in Childhood.

PubMed

Tani, Franca; Ponti, Lucia

2018-01-01

The authors examined how the two different dimensions of guilt feelings, needed for reparation and fear of punishment, could influence social conduct, such as prosocial and aggressive behaviors, and how they are linked to popularity in childhood. The authors hypothesized a theoretical model that they tested, fitting it with empirical data obtained from a sample of 242 Italian children 9-11 years old. Both dimensions of guilt predict prosocial and aggressive behaviors. Specifically, the feeling of guilt linked to the need for reparation tends to negatively predict aggressive behaviors, and positively predict prosocial behaviors. The feeling of guilt linked to the fear of punishment, on the contrary, tends to positively affect aggressive and negatively affect prosocial conducts in children. These results highlight that the different feelings of guilt can represent a relevant risk or protective factor for the development of social competence in childhood. Limitations, strengths, and further development of the present study are discussed.

Understanding the Link between Social Organization and Crime in Rural Communities

PubMed Central

Chilenski, Sarah M.; Syvertsen, Amy K.; Greenberg, Mark T.

2015-01-01

Rural communities make up much of America's heartland, yet we know little about their social organization, and how elements of their social organization relate to crime rates. The current study sought to remedy this gap by examining the associations between two measures of social organization – collective efficacy and social trust – with a number of structural community characteristics, local crime rates, and perceptions of safety in a sample of 27 rural and small town communities in two states. Measures of collective efficacy, social trust, and perceived safety, were gathered from key community members in 2006; other measures were drawn from the 2000 Census and FBI Uniform Crime Reporting system. A series of competing hypotheses were tested to examine the relative importance of social trust and collective efficacy in predicting local crime rates. Results do not support the full generalization of the social disorganization model. Correlational analyses showed that neither collective efficacy nor social trust had a direct association with community crime, nor did they mediate the associations between community structural characteristics and crime. However, perceived safety mediated the association between community crime and both measures of social organization. Analyses suggest that social trust may be more important than collective efficacy when understanding the effect of crime on a community's culture in rural areas. Understanding these associations in rural settings can aid decision makers in shaping policies to reduce crime and juvenile delinquency. PMID:26120326

Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.

PubMed

Crichton, Gamal; Guo, Yufan; Pyysalo, Sampo; Korhonen, Anna

2018-05-21

Link prediction in biomedical graphs has several important applications including predicting Drug-Target Interactions (DTI), Protein-Protein Interaction (PPI) prediction and Literature-Based Discovery (LBD). It can be done using a classifier to output the probability of link formation between nodes. Recently several works have used neural networks to create node representations which allow rich inputs to neural classifiers. Preliminary works were done on this and report promising results. However they did not use realistic settings like time-slicing, evaluate performances with comprehensive metrics or explain when or why neural network methods outperform. We investigated how inputs from four node representation algorithms affect performance of a neural link predictor on random- and time-sliced biomedical graphs of real-world sizes (∼ 6 million edges) containing information relevant to DTI, PPI and LBD. We compared the performance of the neural link predictor to those of established baselines and report performance across five metrics. In random- and time-sliced experiments when the neural network methods were able to learn good node representations and there was a negligible amount of disconnected nodes, those approaches outperformed the baselines. In the smallest graph (∼ 15,000 edges) and in larger graphs with approximately 14% disconnected nodes, baselines such as Common Neighbours proved a justifiable choice for link prediction. At low recall levels (∼ 0.3) the approaches were mostly equal, but at higher recall levels across all nodes and average performance at individual nodes, neural network approaches were superior. Analysis showed that neural network methods performed well on links between nodes with no previous common neighbours; potentially the most interesting links. Additionally, while neural network methods benefit from large amounts of data, they require considerable amounts of computational resources to utilise them. Our results indicate

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.

Disrupted Prediction Error Links Excessive Amygdala Activation to Excessive Fear.

PubMed

Sengupta, Auntora; Winters, Bryony; Bagley, Elena E; McNally, Gavan P

2016-01-13

Basolateral amygdala (BLA) is critical for fear learning, and its heightened activation is widely thought to underpin a variety of anxiety disorders. Here we used chemogenetic techniques in rats to study the consequences of heightened BLA activation for fear learning and memory, and to specifically identify a mechanism linking increased activity of BLA glutamatergic neurons to aberrant fear. We expressed the excitatory hM3Dq DREADD in rat BLA glutamatergic neurons and showed that CNO acted selectively to increase their activity, depolarizing these neurons and increasing their firing rates. This chemogenetic excitation of BLA glutamatergic neurons had no effect on the acquisition of simple fear learning, regardless of whether this learning led to a weak or strong fear memory. However, in an associative blocking task, chemogenetic excitation of BLA glutamatergic neurons yielded significant learning to a blocked conditioned stimulus, which otherwise should not have been learned about. Moreover, in an overexpectation task, chemogenetic manipulation of BLA glutamatergic neurons prevented use of negative prediction error to reduce fear learning, leading to significant impairments in fear inhibition. These effects were not attributable to the chemogenetic manipulation enhancing arousal, increasing asymptotic levels of fear learning or fear memory consolidation. Instead, chemogenetic excitation of BLA glutamatergic neurons disrupted use of prediction error to regulate fear learning. Several neuropsychiatric disorders are characterized by heightened activation of the amygdala. This heightened activation has been hypothesized to underlie increased emotional reactivity, fear over generalization, and deficits in fear inhibition. Yet the mechanisms linking heightened amygdala activation to heightened emotional learning are elusive. Here we combined chemogenetic excitation of rat basolateral amygdala glutamatergic neurons with a variety of behavioral approaches to show that

Predicting dating behavior from aggression and self-perceived social status in adolescence.

PubMed

Lee, Kirsty S; Brittain, Heather; Vaillancourt, Tracy

2018-03-14

We investigated the longitudinal associations between self-reported aggression, self-perceived social status, and dating in adolescence using an intrasexual competition theoretical framework. Participants consisted of 536 students in Grade 9 (age 15), recruited from a community sample, who were assessed on a yearly basis until they were in Grade 11 (age 17). Adolescents self-reported their use of direct and indirect aggression, social status, and number of dating partners. A cross-lagged panel model that controlled for within-time covariance and across-time stability while examining cross-lagged pathways was used to analyze the data. The findings revealed that direct aggression did not predict dating behavior and was negatively associated with self-perceived social status in Grade 10. Self-perceived social status in Grade 9 was positively associated with greater use of indirect aggression in Grade 10. Regarding dating, in Grade 9, self-perceived social status positively predicted more dating partners the following year, while in Grade 10, it was higher levels of indirect aggression that predicted greater dating activity the following year. Overall, there were no significant sex differences in the model. The study supports the utility of evolutionary psychological theory in explaining peer aggression, and suggests that although social status can increase dating opportunities, as adolescents mature, indirect aggression becomes the most successful and strategic means of competing intrasexually and gaining mating advantages. © 2018 Wiley Periodicals, Inc.

The Two-Systems Account of Theory of Mind: Testing the Links to Social- Perceptual and Cognitive Abilities

PubMed Central

Meinhardt-Injac, Bozana; Daum, Moritz M.; Meinhardt, Günter; Persike, Malte

2018-01-01

According to the two-systems account of theory of mind (ToM), understanding mental states of others involves both fast social-perceptual processes, as well as slower, reflexive cognitive operations (Frith and Frith, 2008; Apperly and Butterfill, 2009). To test the respective roles of specific abilities in either of these processes we administered 15 experimental procedures to a large sample of 343 participants, testing ability in face recognition and holistic perception, language, and reasoning. ToM was measured by a set of tasks requiring ability to track and to infer complex emotional and mental states of others from faces, eyes, spoken language, and prosody. We used structural equation modeling to test the relative strengths of a social-perceptual (face processing related) and reflexive-cognitive (language and reasoning related) path in predicting ToM ability. The two paths accounted for 58% of ToM variance, thus validating a general two-systems framework. Testing specific predictor paths revealed language and face recognition as strong and significant predictors of ToM. For reasoning, there were neither direct nor mediated effects, albeit reasoning was strongly associated with language. Holistic face perception also failed to show a direct link with ToM ability, while there was a mediated effect via face recognition. These results highlight the respective roles of face recognition and language for the social brain, and contribute closer empirical specification of the general two-systems account. PMID:29445336

Linking Local Food Systems and the Social Economy? Future Roles for Farmers' Markets in Alberta and British Columbia

ERIC Educational Resources Information Center

Wittman, Hannah; Beckie, Mary; Hergesheimer, Chris

2012-01-01

Often organized as grassroots, nonprofit organizations, many farmers' markets serve as strategic venues linking producers and consumers of local food while fulfilling multiple social, economic, and environmental objectives. This article examines the potential of farmers' markets to play a catalyst role in linking local food systems to the social…

Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

PubMed Central

Doehrmann, Oliver; Ghosh, Satrajit S.; Polli, Frida E.; Reynolds, Gretchen O.; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M.; Whitfield-Gabrieli, Susan; Hofmann, Stefan G.; Pollack, Mark; Gabrieli, John D.

2013-01-01

Context Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. Objective To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Design Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Setting Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Patients Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Interventions Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Main Outcome Measures Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Results Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. Conclusions The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized

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.

Peer Victimization and Social Alienation: Predicting Deviant Peer Affiliation in Middle School

PubMed Central

Rudolph, Karen D.; Lansford, Jennifer E.; Agoston, Anna Monica; Sugimura, Niwako; Schwartz, David; Dodge, Kenneth A.; Pettit, Gregory S.; Bates, John E.

2013-01-01

Two prospective studies examined a theoretical model wherein exposure to victimization, resulting from early behavioral risk, heightens children’s social alienation and subsequent deviant peer affiliation (DPA). Across Study 1 (298 girls, 287 boys; K – 7th grade; 5 – 12 years) and Study 2 (338 girls, 298 boys; 2nd – 6th grade; 7 – 11 years), children, parents, peers, and teachers reported on children’s externalizing behavior and internalizing symptoms, peer victimization, social alienation, and DPA. Path analyses supported the proposed pathway: Peer victimization predicted social alienation, which then predicted DPA. Early externalizing behavior set this path in motion and made an independent contribution to DPA. This research identifies an important pathway through which externalizing behavior and consequent peer victimization launch children onto a risky social trajectory. PMID:23621796

Culture shapes whether the pursuit of happiness predicts higher or lower well-being

PubMed Central

Ford, Brett Q.; Dmitrieva, Julia O.; Heller, Daniel; Chentsova-Dutton, Yulia; Grossmann, Igor; Tamir, Maya; Uchida, Yukiko; Koopmann-Holm, Birgit; Floerke, Victoria A.; Uhrig, Meike; Bokhan, Tatiana; Mauss, Iris B.

2015-01-01

Pursuing happiness can paradoxically impair well-being. Here, we propose the potential downsides to pursuing happiness may be specific to individualistic cultures. In collectivistic (vs. individualistic) cultures, pursuing happiness may be more successful because happiness is viewed – and thus pursued – in relatively socially-engaged ways. In four geographical regions that vary in level of collectivism (U.S., Germany, Russia, East Asia), we assessed participants’ well-being, motivation to pursue happiness, and to what extent they pursued happiness in socially-engaged ways. Motivation to pursue happiness predicted lower well-being in the U.S., did not predict well-being in Germany, and predicted higher well-being in Russia and in East Asia. These cultural differences in the link between motivation to pursue happiness and well-being were explained by cultural differences in the socially-engaged pursuit of happiness. These findings suggest that culture shapes whether the pursuit of happiness is linked with better or worse well-being, perhaps via how people pursue happiness. PMID:26347945

Bechstein's bats maintain individual social links despite a complete reorganisation of their colony structure

NASA Astrophysics Data System (ADS)

Baigger, A.; Perony, N.; Reuter, M.; Leinert, V.; Melber, M.; Grünberger, S.; Fleischmann, D.; Kerth, G.

2013-09-01

Several social mammals, including elephants and some primates, whales and bats, live in multilevel societies that form temporary subgroups. Despite these fission-fusion dynamics, group members often maintain long-term bonds. However, it is unclear whether such individual links and the resulting stable social subunits continue to exist after a complete reorganisation of a society, e.g. following a population crash. Here, we employed a weighted network analysis on 7,109 individual roosting records collected over 4 years in a wild Bechstein's bat colony. We show that, in response to a strong population decline, the colony's two stable social subunits fused into a non-modular social network. Nevertheless, in the first year after the crash, long-term bonds were still detectable, suggesting that the bats remembered previous individual relationships. Our findings are important for understanding the flexibility of animal societies in the face of dramatic changes and for the conservation of social mammals with declining populations.

Bechstein's bats maintain individual social links despite a complete reorganisation of their colony structure.

PubMed

Baigger, A; Perony, N; Reuter, M; Leinert, V; Melber, M; Grünberger, S; Fleischmann, D; Kerth, G

2013-09-01

Several social mammals, including elephants and some primates, whales and bats, live in multilevel societies that form temporary subgroups. Despite these fission-fusion dynamics, group members often maintain long-term bonds. However, it is unclear whether such individual links and the resulting stable social subunits continue to exist after a complete reorganisation of a society, e.g. following a population crash. Here, we employed a weighted network analysis on 7,109 individual roosting records collected over 4 years in a wild Bechstein's bat colony. We show that, in response to a strong population decline, the colony's two stable social subunits fused into a non-modular social network. Nevertheless, in the first year after the crash, long-term bonds were still detectable, suggesting that the bats remembered previous individual relationships. Our findings are important for understanding the flexibility of animal societies in the face of dramatic changes and for the conservation of social mammals with declining populations.

What Factors Predict Who Will Have a Strong Social Network Following a Stroke?

ERIC Educational Resources Information Center

Northcott, Sarah; Marshall, Jane; Hilari, Katerina

2016-01-01

Purpose: Measures of social networks assess the number and nature of a person's social contacts, and strongly predict health outcomes. We explored how social networks change following a stroke and analyzed concurrent and baseline predictors of social networks 6 months poststroke. Method: We conducted a prospective longitudinal observational study.…

Maladaptive social information processing in childhood predicts young men's atypical amygdala reactivity to threat.

PubMed

Choe, Daniel Ewon; Shaw, Daniel S; Forbes, Erika E

2015-05-01

Maladaptive social information processing, such as hostile attributional bias and aggressive response generation, is associated with childhood maladjustment. Although social information processing problems are correlated with heightened physiological responses to social threat, few studies have examined their associations with neural threat circuitry, specifically amygdala activation to social threat. A cohort of 310 boys participated in an ongoing longitudinal study and completed questionnaires and laboratory tasks assessing their social and cognitive characteristics the boys were between 10 and 12 years of age. At age 20, 178 of these young men underwent functional magnetic resonance imaging and a social threat task. At age 22, adult criminal arrest records and self-reports of impulsiveness were obtained. Path models indicated that maladaptive social information-processing at ages 10 and 11 predicted increased left amygdala reactivity to fear faces, an ambiguous threat, at age 20 while accounting for childhood antisocial behavior, empathy, IQ, and socioeconomic status. Exploratory analyses indicated that aggressive response generation - the tendency to respond to threat with reactive aggression - predicted left amygdala reactivity to fear faces and was concurrently associated with empathy, antisocial behavior, and hostile attributional bias, whereas hostile attributional bias correlated with IQ. Although unrelated to social information-processing problems, bilateral amygdala reactivity to anger faces at age 20 was unexpectedly predicted by low IQ at age 11. Amygdala activation did not mediate associations between social information processing and number of criminal arrests, but both impulsiveness at age 22 and arrests were correlated with right amygdala reactivity to anger facial expressions at age 20. Childhood social information processing and IQ predicted young men's amygdala response to threat a decade later, which suggests that childhood social

A Social Psychological Model for Predicting Sexual Harassment.

ERIC Educational Resources Information Center

Pryor, John B.; And Others

1995-01-01

Presents a Person X Situation (PXS) model of sexual harassment suggesting that sexually harassing behavior may be predicted from an analysis of social situational and personal factors. Research on sexual harassment proclivities in men is reviewed, and a profile of men who have a high a likelihood to sexually harass is discussed. Possible PXS…

Conflict Prediction Through Geo-Spatial Interpolation of Radicalization in Syrian Social Media

DTIC Science & Technology

2015-09-24

TRAC-M-TM-15-031 September 2015 Conflict Prediction Through Geo-Spatial Interpolation of Radicalization in Syrian Social Media ...Spatial Interpolation of Radicalization in Syrian Social Media Authors MAJ Adam Haupt Dr. Camber Warren...Spatial Interpolation of Radicalization in Syrian Social 1RAC Project Code 060114 Media 6. AUTHOR(S) MAJ Haupt, Dr. Warren 7. PERFORMING OR

Peer victimization and social alienation: predicting deviant peer affiliation in middle school.

PubMed

Rudolph, Karen D; Lansford, Jennifer E; Agoston, Anna M; Sugimura, Niwako; Schwartz, David; Dodge, Kenneth A; Pettit, Gregory S; Bates, John E

2014-01-01

Two prospective studies examined a theoretical model wherein exposure to victimization, resulting from early behavioral risk, heightens children's social alienation and subsequent deviant peer affiliation (DPA). Across Study 1 (298 girls, 287 boys; K-7th grade; 5-12 years) and Study 2 (338 girls, 298 boys; 2nd-6th grade; 8-12 years), children, parents, peers, and teachers reported on children's externalizing behavior and internalizing symptoms, peer victimization, social alienation, and DPA. Path analyses supported the proposed pathway: Peer victimization predicted social alienation, which then predicted DPA. Early externalizing behavior set this path in motion and made an independent contribution to DPA. This research identifies an important pathway through which externalizing behavior and consequent peer victimization launch children onto a risky social trajectory. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

Teacher characteristics, social classroom relationships, and children's social, emotional, and behavioral classroom adjustment in special education.

PubMed

Breeman, L D; Wubbels, T; van Lier, P A C; Verhulst, F C; van der Ende, J; Maras, A; Hopman, J A B; Tick, N T

2015-02-01

The goal of this study was to explore relations between teacher characteristics (i.e., competence and wellbeing); social classroom relationships (i.e., teacher-child and peer interactions); and children's social, emotional, and behavioral classroom adjustment. These relations were explored at both the individual and classroom levels among 414 children with emotional and behavioral disorders placed in special education. Two models were specified. In the first model, children's classroom adjustment was regressed on social relationships and teacher characteristics. In the second model, reversed links were examined by regressing teacher characteristics on social relationships and children's adjustment. Results of model 1 showed that, at the individual level, better social and emotional adjustment of children was predicted by higher levels of teacher-child closeness and better behavioral adjustment was predicted by both positive teacher-child and peer interactions. At the classroom level, positive social relationships were predicted by higher levels of teacher competence, which in turn were associated with lower classroom levels of social problems. Higher levels of teacher wellbeing were directly associated with classroom adaptive and maladaptive child outcomes. Results of model 2 showed that, at the individual and classroom levels, only the emotional and behavioral problems of children predicted social classroom relationships. At the classroom level, teacher competence was best predicted by positive teacher-child relationships and teacher wellbeing was best predicted by classroom levels of prosocial behavior. We discuss the importance of positive teacher-child and peer interactions for children placed in special education and suggest ways of improving classroom processes by targeting teacher competence. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Neural mechanisms of the link between giving social support and health.

PubMed

Inagaki, Tristen K

2018-05-11

Giving social support to others has emerged as an additional route by which social ties influence health. Thus, giving support to others not only influences the health of the individual receiving support, but also the health of the individual giving the support. However, the neural mechanisms by which giving support leads to health are only beginning to be explored. In hopes of consolidating and guiding future research on giving support and health, the current review considers why, how, and when giving support is health promoting. Special emphasis is placed on neural regions known to contribute to parental care in animals that both reinforce giving support behavior (ventral striatum and septal area) and reduce stress-related responding (e.g., amygdala) to facilitate care. Hypothesized links between neural regions involved in giving support and peripheral physiology (sympathetic nervous system, hypothalamic-pituitary-adrenal axis, and related inflammatory responding) are considered as well as the conditions under which giving support should be most beneficial for health. Finally, the implications of the current perspective for understanding how social relationships, more broadly, contribute to health and suggestions for future directions are offered. © 2018 New York Academy of Sciences.

Digging deeper into the link between socio-cognitive ability and social relationships.

PubMed

Mizokawa, Ai; Koyasu, Masuo

2015-03-01

In this commentary on 'Friendlessness and theory of mind: A prospective longitudinal study' by Fink, Begeer, Peterson, Slaughter, and de Rosnay (Brit. J. Dev. Psychol, 2015; 33, 1-17) we reconsider the link between early mastery of theory of mind (ToM) and social relationships by focusing on connections with other related areas of socio-cognitive ability such as emotional competence, ToM development across age, and the effect of interventions. © 2014 The British Psychological Society.

Linking Teacher Socialization Research with a PETE Program: Insights from Beginning and Experienced Teachers

ERIC Educational Resources Information Center

MacPhail, Ann; Hartley, Therese

2016-01-01

The purpose of this study is to explore the extent to which beginning and experienced teachers differed in their perceptions of shaping school forces and their being shaped by school forces. The findings allow the authors to examine the link between teacher socialization research and practice in a physical education teacher education (PETE)…

Perceived support from a caregiver's social ties predicts subsequent care-recipient health.

PubMed

Kelley, Dannielle E; Lewis, Megan A; Southwell, Brian G

2017-12-01

Most social support research has examined support from an individual patient perspective and does not model the broader social context of support felt by caregivers. Understanding how social support networks may complement healthcare services is critical, considering the aging population, as social support networks may be a valuable resource to offset some of the demands placed on the healthcare system. We sought to identify how caregivers' perceived organizational and interpersonal support from their social support network influences care-recipient health. We created a dyadic dataset of care-recipient and caregivers from the first two rounds of the National Health and Aging Trends survey (2011, 2012) and the first round of the associated National Study of Caregivers survey (2011). Using structural equation modeling, we explored how caregivers' perceived social support is associated with caregiver confidence to provide care, and is associated with care-recipient health outcomes at two time points. All data were analyzed in 2016. Social engagement with members from caregivers' social support networks was positively associated with caregiver confidence, and social engagement and confidence were positively associated with care-recipient health at time 1. Social engagement positively predicted patient health at time 2 controlling for time 1. Conversely, use of organizational support negatively predicted care-recipient health at time 2. Care-recipients experience better health outcomes when caregivers are able to be more engaged with members of their social support network.

Incorporating the Last Four Digits of Social Security Numbers Substantially Improves Linking Patient Data from De-identified Hospital Claims Databases.

PubMed

Naessens, James M; Visscher, Sue L; Peterson, Stephanie M; Swanson, Kristi M; Johnson, Matthew G; Rahman, Parvez A; Schindler, Joe; Sonneborn, Mark; Fry, Donald E; Pine, Michael

2015-08-01

Assess algorithms for linking patients across de-identified databases without compromising confidentiality. Hospital discharges from 11 Mayo Clinic hospitals during January 2008-September 2012 (assessment and validation data). Minnesota death certificates and hospital discharges from 2009 to 2012 for entire state (application data). Cross-sectional assessment of sensitivity and positive predictive value (PPV) for four linking algorithms tested by identifying readmissions and posthospital mortality on the assessment data with application to statewide data. De-identified claims included patient gender, birthdate, and zip code. Assessment records were matched with institutional sources containing unique identifiers and the last four digits of Social Security number (SSNL4). Gender, birthdate, and five-digit zip code identified readmissions with a sensitivity of 98.0 percent and a PPV of 97.7 percent and identified postdischarge mortality with 84.4 percent sensitivity and 98.9 percent PPV. Inclusion of SSNL4 produced nearly perfect identification of readmissions and deaths. When applied statewide, regions bordering states with unavailable hospital discharge data had lower rates. Addition of SSNL4 to administrative data, accompanied by appropriate data use and data release policies, can enable trusted repositories to link data with nearly perfect accuracy without compromising patient confidentiality. States maintaining centralized de-identified databases should add SSNL4 to data specifications. © Health Research and Educational Trust.

Incorporating the Last Four Digits of Social Security Numbers Substantially Improves Linking Patient Data from De-identified Hospital Claims Databases

PubMed Central

Naessens, James M; Visscher, Sue L; Peterson, Stephanie M; Swanson, Kristi M; Johnson, Matthew G; Rahman, Parvez A; Schindler, Joe; Sonneborn, Mark; Fry, Donald E; Pine, Michael

2015-01-01

Objective Assess algorithms for linking patients across de-identified databases without compromising confidentiality. Data Sources/Study Setting Hospital discharges from 11 Mayo Clinic hospitals during January 2008–September 2012 (assessment and validation data). Minnesota death certificates and hospital discharges from 2009 to 2012 for entire state (application data). Study Design Cross-sectional assessment of sensitivity and positive predictive value (PPV) for four linking algorithms tested by identifying readmissions and posthospital mortality on the assessment data with application to statewide data. Data Collection/Extraction Methods De-identified claims included patient gender, birthdate, and zip code. Assessment records were matched with institutional sources containing unique identifiers and the last four digits of Social Security number (SSNL4). Principal Findings Gender, birthdate, and five-digit zip code identified readmissions with a sensitivity of 98.0 percent and a PPV of 97.7 percent and identified postdischarge mortality with 84.4 percent sensitivity and 98.9 percent PPV. Inclusion of SSNL4 produced nearly perfect identification of readmissions and deaths. When applied statewide, regions bordering states with unavailable hospital discharge data had lower rates. Conclusion Addition of SSNL4 to administrative data, accompanied by appropriate data use and data release policies, can enable trusted repositories to link data with nearly perfect accuracy without compromising patient confidentiality. States maintaining centralized de-identified databases should add SSNL4 to data specifications. PMID:26073819

The proactive brain: memory for predictions

PubMed Central

Bar, Moshe

2009-01-01

It is proposed that the human brain is proactive in that it continuously generates predictions that anticipate the relevant future. In this proposal, analogies are derived from elementary information that is extracted rapidly from the input, to link that input with the representations that exist in memory. Finding an analogical link results in the generation of focused predictions via associative activation of representations that are relevant to this analogy, in the given context. Predictions in complex circumstances, such as social interactions, combine multiple analogies. Such predictions need not be created afresh in new situations, but rather rely on existing scripts in memory, which are the result of real as well as of previously imagined experiences. This cognitive neuroscience framework provides a new hypothesis with which to consider the purpose of memory, and can help explain a variety of phenomena, ranging from recognition to first impressions, and from the brain's ‘default mode’ to a host of mental disorders. PMID:19528004

Racial and ethnic socialization as moderators of racial discrimination and school adjustment of adopted and nonadopted Korean American adolescents.

PubMed

Seol, Kyoung Ok; Yoo, Hyung Chol; Lee, Richard M; Park, Ji Eun; Kyeong, Yena

2016-04-01

This study investigated the roles of racial and ethnic socialization in the link between racial discrimination and school adjustment among a sample of 233 adopted Korean American adolescents from White adoptive families and 155 nonadopted Korean American adolescents from immigrant Korean families. Adopted Korean American adolescents reported lower levels of racial discrimination, racial socialization, and ethnic socialization than nonadopted Korean American adolescents. However, racial discrimination was negatively related to school belonging and school engagement, and ethnic socialization was positively related to school engagement for both groups. Racial socialization also had a curvilinear relationship with school engagement for both groups. A moderate level of racial socialization predicted positive school engagement, whereas low and high levels of racial socialization predicted negative school engagement. Finally, ethnic socialization moderated the link between racial discrimination and school belonging, which differed between groups. In particular, ethnic socialization exacerbated the relations between racial discrimination and school belonging for adopted Korean American adolescents, whereas ethnic socialization buffered this link for nonadopted Korean American adolescents. The findings illustrate the complex relationship between racial and ethnic socialization, racial discrimination, and school adjustment. (c) 2016 APA, all rights reserved).

An examination of social capital and social disorganisation in neighbourhoods in the British household panel study.

PubMed

McCulloch, Andrew

2003-04-01

Recent developments in social science research suggest that social environmental factors may be important for explaining community variations in health. We investigate the structural sources of two mechanisms that produce community variations in health. Using survey data collected from a representative cross-section of British households we examine variations in neighbourhood social capital and neighbourhood social disorganisation across a sample of British neighbourhoods. Adjusting for respondent's attributes, we assess the effects of neighbourhood characteristics measured by the 1991 census in Britain. The results show that concentrated affluence, residential instability and ethnic heterogeneity predict social capital for women. Population density is the only neighbourhood characteristic to predict social capital for men. For both men and women concentrated disadvantage and population density are associated with social disorganisation. Residential instability is additionally associated with social disorganisation for women. For women it was found that neighbourhood characteristics interact with individual social class in accounting for variations in social capital, the effects of neighbourhood characteristics being larger for those in professional and managerial and skilled non-manual occupations. The results show that neighbourhood structural characteristics influence social organisation processes. This helps establish a link between the structural characteristics of neighbourhoods and individual health outcomes.

Leveraging Social Networking Technologies: An Analysis of the Knowledge Flows Facilitated by Social Media and the Potential Improvements in Situational Awareness, Readiness, and Productivity

DTIC Science & Technology

2010-09-01

articulating perception, interpretation and actionable prediction in an operational environment . BCKS’ success with digital storytelling has far...podcasts; wikis and other collaborative spaces; social networks such as Facebook and LinkedIn; other user generated content; virtual social environments ...study of Xerox’s knowledge management systems noting that 80% of its IT was focused on adapting to the social dynamics of its workplace environment

Culture and Social Relationship as Factors of Affecting Communicative Non-verbal Behaviors

NASA Astrophysics Data System (ADS)

Akhter Lipi, Afia; Nakano, Yukiko; Rehm, Mathias

The goal of this paper is to link a bridge between social relationship and cultural variation to predict conversants' non-verbal behaviors. This idea serves as a basis of establishing a parameter based socio-cultural model, which determines non-verbal expressive parameters that specify the shapes of agent's nonverbal behaviors in HAI. As the first step, a comparative corpus analysis is done for two cultures in two specific social relationships. Next, by integrating the cultural and social parameters factors with the empirical data from corpus analysis, we establish a model that predicts posture. The predictions from our model successfully demonstrate that both cultural background and social relationship moderate communicative non-verbal behaviors.

Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants.

PubMed

Trujillo, Sandra P; Valencia, Stella; Trujillo, Natalia; Ugarriza, Juan E; Rodríguez, Mónica V; Rendón, Jorge; Pineda, David A; López, José D; Ibañez, Agustín; Parra, Mario A

2017-01-01

Emotional processing (EP) is crucial for the elaboration and implementation of adaptive social strategies. EP is also necessary for the expression of social cognition and behavior (SCB) patterns. It is well-known that war contexts induce socio-emotional atypical functioning, in particular for those who participate in combats. Thus, ex-combatants represent an ideal non-clinical population to explore EP modulation and to evaluate its relation with SCB. The aim of this study was to explore EP and its relation with SCB dimensions such as empathy, theory of mind and social skills in a sample of 50 subjects, of which 30 were ex-combatants from illegally armed groups in Colombia, and 20 controls without combat experience. We adapted an Emotional Recognition Task for faces and words and synchronized it with electroencephalographic recording. Ex-combatants presented with higher assertion skills and showed more pronounced brain responses to faces than Controls. They did not show the bias toward anger observed in control participants whereby the latter group was more likely to misclassify neutral faces as angry. However, ex-combatants showed an atypical word valence processing. That is, words with different emotions yielded no differences in N170 modulations. SCB variables were successfully predicted by neurocognitive variables. Our results suggest that in ex-combatants the links between EP and SCB functions are reorganized. This may reflect neurocognitive modulations associated to chronic exposure to war experiences.

Atypical Modulations of N170 Component during Emotional Processing and Their Links to Social Behaviors in Ex-combatants

PubMed Central

Trujillo, Sandra P.; Valencia, Stella; Trujillo, Natalia; Ugarriza, Juan E.; Rodríguez, Mónica V.; Rendón, Jorge; Pineda, David A.; López, José D.; Ibañez, Agustín; Parra, Mario A.

2017-01-01

Emotional processing (EP) is crucial for the elaboration and implementation of adaptive social strategies. EP is also necessary for the expression of social cognition and behavior (SCB) patterns. It is well-known that war contexts induce socio-emotional atypical functioning, in particular for those who participate in combats. Thus, ex-combatants represent an ideal non-clinical population to explore EP modulation and to evaluate its relation with SCB. The aim of this study was to explore EP and its relation with SCB dimensions such as empathy, theory of mind and social skills in a sample of 50 subjects, of which 30 were ex-combatants from illegally armed groups in Colombia, and 20 controls without combat experience. We adapted an Emotional Recognition Task for faces and words and synchronized it with electroencephalographic recording. Ex-combatants presented with higher assertion skills and showed more pronounced brain responses to faces than Controls. They did not show the bias toward anger observed in control participants whereby the latter group was more likely to misclassify neutral faces as angry. However, ex-combatants showed an atypical word valence processing. That is, words with different emotions yielded no differences in N170 modulations. SCB variables were successfully predicted by neurocognitive variables. Our results suggest that in ex-combatants the links between EP and SCB functions are reorganized. This may reflect neurocognitive modulations associated to chronic exposure to war experiences. PMID:28588462

Family cumulative risk and at-risk kindergarteners' social competence: the mediating role of parent representations of the attachment relationship.

PubMed

Sparks, Lauren A; Trentacosta, Christopher J; Owusu, Erika; McLear, Caitlin; Smith-Darden, Joanne

2018-08-01

Secure attachment relationships have been linked to social competence in at-risk children. In the current study, we examined the role of parent secure base scripts in predicting at-risk kindergarteners' social competence. Parent representations of secure attachment were hypothesized to mediate the relationship between lower family cumulative risk and children's social competence. Participants included 106 kindergarteners and their primary caregivers recruited from three urban charter schools serving low-income families as a part of a longitudinal study. Lower levels of cumulative risk predicted greater secure attachment representations in parents, and scores on the secure base script assessment predicted children's social competence. An indirect relationship between lower cumulative risk and kindergarteners' social competence via parent secure base script scores was also supported. Parent script-based representations of the attachment relationship appear to be an important link between lower levels of cumulative risk and low-income kindergarteners' social competence. Implications of these findings for future interventions are discussed.

Network centrality and seasonality interact to predict lice load in a social primate

PubMed Central

Duboscq, Julie; Romano, Valeria; Sueur, Cédric; MacIntosh, Andrew J.J.

2016-01-01

Lice are socially-transmitted ectoparasites. Transmission depends upon their host’s degree of contact with conspecifics. While grooming facilitates ectoparasite transmission via body contact, it also constrains their spread through parasite removal. We investigated relations between parasite burden and sociality in female Japanese macaques following two opposing predictions: i) central females in contact/grooming networks harbour more lice, related to their numerous contacts; ii) central females harbour fewer lice, related to receiving more grooming. We estimated lice load non-invasively using the conspicuous louse egg-picking behaviour performed by macaques during grooming. We tested for covariation in several centrality measures and lice load, controlling for season, female reproductive state and dominance rank. Results show that the interaction between degree centrality (number of partners) and seasonality predicted lice load: females interacting with more partners had fewer lice than those interacting with fewer partners in winter and summer, whereas there was no relationship between lice load and centrality in spring and fall. This is counter to the prediction that increased contact leads to greater louse burden but fits the prediction that social grooming limits louse burden. Interactions between environmental seasonality and both parasite and host biology appeared to mediate the role of social processes in louse burden. PMID:26915589

Network centrality and seasonality interact to predict lice load in a social primate.

PubMed

Duboscq, Julie; Romano, Valeria; Sueur, Cédric; MacIntosh, Andrew J J

2016-02-26

Lice are socially-transmitted ectoparasites. Transmission depends upon their host's degree of contact with conspecifics. While grooming facilitates ectoparasite transmission via body contact, it also constrains their spread through parasite removal. We investigated relations between parasite burden and sociality in female Japanese macaques following two opposing predictions: i) central females in contact/grooming networks harbour more lice, related to their numerous contacts; ii) central females harbour fewer lice, related to receiving more grooming. We estimated lice load non-invasively using the conspicuous louse egg-picking behaviour performed by macaques during grooming. We tested for covariation in several centrality measures and lice load, controlling for season, female reproductive state and dominance rank. Results show that the interaction between degree centrality (number of partners) and seasonality predicted lice load: females interacting with more partners had fewer lice than those interacting with fewer partners in winter and summer, whereas there was no relationship between lice load and centrality in spring and fall. This is counter to the prediction that increased contact leads to greater louse burden but fits the prediction that social grooming limits louse burden. Interactions between environmental seasonality and both parasite and host biology appeared to mediate the role of social processes in louse burden.

Social nature of eating could explain missing link between food insecurity and childhood obesity.

PubMed

Mata, Jutta; Dallacker, Mattea; Hertwig, Ralph

2017-01-01

We suggest that social factors are key to explain the missing link between food insecurity and obesity in children. Parents and public institutions are children's nutritional gatekeepers. They protect children from food insecurity by trimming down their consumption or by institutional support. To gauge children's food insecurity, evaluations across the different nutritional gatekeepers need to be integrated.

Racial and Ethnic Socialization as Moderators of Racial Discrimination and School Adjustment of Adopted and Non-adopted Korean American Adolescents

PubMed Central

Seol, Kyoung Ok; Yoo, Hyung Chol; Lee, Richard M.; Park, Ji Eun; Kyeong, Yena

2015-01-01

This study investigated roles of racial and ethnic socialization in the link between racial discrimination and school adjustment among a sample of 233 adopted Korean American adolescents from White adoptive families and 155 non-adopted Korean American adolescents from immigrant Korean families. Adopted Korean American adolescents reported lower levels of racial discrimination, racial socialization, and ethnic socialization than non-adopted Korean American adolescents. However, racial discrimination was negatively related to school belonging and school engagement, and ethnic socialization was positively related to school engagement for both groups. Racial socialization also had a curvilinear relationship with school engagement for both groups. Moderate level of racial socialization predicted positive school engagement, whereas low and high levels of racial socialization predicted negative school engagement. Finally, ethnic socialization moderated the link between racial discrimination and school belonging, which differed between groups. In particular, ethnic socialization exacerbated the relations between racial discrimination and school belonging for adopted Korean American adolescents, whereas, ethnic socialization buffered this link for non-adopted Korean American adolescents. Findings illustrate the complex relationship between racial and ethnic socialization, racial discrimination, and school adjustment. PMID:26479418

Links between local language competence and peer relations among Swiss and immigrant children: the mediating role of social behavior.

PubMed

von Grünigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Françoise D

2012-04-01

The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports on 541 (286 boys and 255 girls) immigrant and Swiss native 5-to-6 year-old kindergarteners. Results showed the immigrant children were less fluent in the local language compared to native Swiss classmates. Moreover, results from structural equation models, with bootstrap tests of indirect effects, indicated that social behaviors mediated the link between LLC and the quality of children's peer relationships. Implications of these findings for school professionals are discussed, such as the need to help immigrant children make a smoother transition to their host communities by providing additional language and social supports while children acculturate and acclimate to their new surroundings and peer group. Published by Elsevier Ltd.

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ1 Regularization

PubMed Central

Sanchez-Perez, Gabriel; Toscano-Medina, Karina; Martinez-Hernandez, Victor; Olivares-Mercado, Jesus; Sanchez, Victor

2018-01-01

In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ1 regularization. PMID:29710833

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ₁ Regularization.

PubMed

Hernandez-Suarez, Aldo; Sanchez-Perez, Gabriel; Toscano-Medina, Karina; Martinez-Hernandez, Victor; Perez-Meana, Hector; Olivares-Mercado, Jesus; Sanchez, Victor

2018-04-29

In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ 1 regularization.

Social Inclusion Predicts Lower Blood Glucose and Low-Density Lipoproteins in Healthy Adults.

PubMed

Floyd, Kory; Veksler, Alice E; McEwan, Bree; Hesse, Colin; Boren, Justin P; Dinsmore, Dana R; Pavlich, Corey A

2017-08-01

Loneliness has been shown to have direct effects on one's personal well-being. Specifically, a greater feeling of loneliness is associated with negative mental health outcomes, negative health behaviors, and an increased likelihood of premature mortality. Using the neuroendocrine hypothesis, we expected social inclusion to predict decreases in both blood glucose levels and low-density lipoproteins (LDLs) and increases in high-density lipoproteins (HDLs). Fifty-two healthy adults provided self-report data for social inclusion and blood samples for hematological tests. Results indicated that higher social inclusion predicted lower levels of blood glucose and LDL, but had no effect on HDL. Implications for theory and practice are discussed.

Agentic personality as mediator of social capital on developmental outcomes in the transition to adulthood: Evidence from Shanghai, China.

PubMed

Yuan, Rui; Ngai, Steven Sek-yum

2016-01-01

Drawing upon a sample of 1153 young people in Shanghai, China, this study investigates how agentic personality mediates between social capital embedded in a range of social contexts (family, friendship, association, and linking connection) and developmental outcomes during the transition to adulthood. The results of a structural equation modeling (SEM) analysis provide a good fit for the sample as a whole. The overall findings support the hypotheses that a higher level of agentic personality, including resilience, self-efficacy, and self-esteem, is associated with higher levels of developmental outcomes. Agentic personality also mediates the effects of family, friendship, associational, and linking social capital on developmental outcomes. Family social capital is predictive of university students' identity achievement and academic achievement, but not of their mental health. Linking social capital is only predictive of identity achievement. Unexpectedly, friendship social capital and associational social capital are predictive of a lower level of academic achievement and mental health, respectively, despite their positive influences on all three developmental outcomes through their significant effects on agentic personality. The study provides empirical support for the importance of social capital in promoting young people's transition to adulthood. Implications for theory, practice, and policy are also discussed. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

ERIC Educational Resources Information Center

Lee, Diane Sookyoung; Padilla, Amado M.

2016-01-01

This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

When opportunity meets motivation: Neural engagement during social approach is linked to high approach motivation.

PubMed

Radke, Sina; Seidel, Eva-Maria; Eickhoff, Simon B; Gur, Ruben C; Schneider, Frank; Habel, Ute; Derntl, Birgit

2016-02-15

Social rewards are processed by the same dopaminergic-mediated brain networks as non-social rewards, suggesting a common representation of subjective value. Individual differences in personality and motivation influence the reinforcing value of social incentives, but it remains open whether the pursuit of social incentives is analogously supported by the neural reward system when positive social stimuli are connected to approach behavior. To test for a modulation of neural activation by approach motivation, individuals with high and low approach motivation (BAS) completed implicit and explicit social approach-avoidance paradigms during fMRI. High approach motivation was associated with faster implicit approach reactions as well as a trend for higher approach ratings, indicating increased approach tendencies. Implicit and explicit positive social approach was accompanied by stronger recruitment of the nucleus accumbens, middle cingulate cortex, and (pre-)cuneus for individuals with high compared to low approach motivation. These results support and extend prior research on social reward processing, self-other distinctions and affective judgments by linking approach motivation to the engagement of reward-related circuits during motivational reactions to social incentives. This interplay between motivational preferences and motivational contexts might underlie the rewarding experience during social interactions. Copyright © 2015 Elsevier Inc. All rights reserved.

Using Emotional and Social Factors To Predict Student Success.

ERIC Educational Resources Information Center

Pritchard, Mary E.; Wilson, Gregory S.

2003-01-01

College academic success and retention have traditionally been predicted using demographic and academic variables. This study moved beyond traditional predictors. A survey of 218 undergraduate students revealed that emotional and social factors (e.g., stress, frequency of alcohol consumption) related to GPA and emotional factors (e.g.,…

Links between Local Language Competence and Peer Relations among Swiss and Immigrant Children: The Mediating Role of Social Behavior

ERIC Educational Resources Information Center

von Grunigen, Renate; Kochenderfer-Ladd, Becky; Perren, Sonja; Alsaker, Francoise D.

2012-01-01

The primary aim of this investigation was to evaluate a model in which children's social behaviors, including prosocial behavior, setting limits, and social withdrawal, were hypothesized to mediate the links between local language competence (LLC) and peer acceptance and victimization. Longitudinal data were collected via teacher and peer reports…

Maladaptive social information processing in childhood predicts young men’s atypical amygdala reactivity to threat

PubMed Central

Choe, Daniel Ewon; Shaw, Daniel S.; Forbes, Erika E.

2014-01-01

Background Maladaptive social information processing, such as hostile attributional bias and aggressive response generation, is associated with childhood maladjustment. Although social information processing problems are correlated with heightened physiological responses to social threat, few studies have examined their associations with neural threat circuitry, specifically amygdala activation to social threat. Methods A cohort of 310 boys participated in an ongoing longitudinal study and completed questionnaires and laboratory tasks assessing their social and cognitive characteristics between 10- and 12-years-old. At age 20, 178 of these young men underwent functional magnetic resonance imaging and a social threat task. At age 22, adult criminal arrest records and self-reports of impulsiveness were obtained. Results Path models indicated that maladaptive social information processing at ages 10 and 11 predicted increased left amygdala reactivity to fear faces, an ambiguous threat, at age 20 while accounting for childhood antisocial behavior, empathy, IQ, and socioeconomic status. Exploratory analyses indicated that aggressive response generation—the tendency to respond to threat with reactive aggression—predicted left amygdala reactivity to fear faces and was concurrently associated with empathy, antisocial behavior, and hostile attributional bias, whereas hostile attributional bias correlated with IQ. Although unrelated to social information processing problems, bilateral amygdala reactivity to anger faces at age 20 was unexpectedly predicted by low IQ at age 11. Amygdala activation did not mediate associations between social information processing and number of criminal arrests, but both impulsiveness at age 22 and arrests were correlated with right amygdala reactivity to anger facial expressions at age 20. Conclusions Childhood social information processing and IQ predicted young men’s amygdala response to threat a decade later, which suggests that

Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance.

PubMed

Wong, Aaron L; Shelhamer, Mark

2014-05-01

Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation. Copyright © 2014 the American Physiological Society.

Identifying social factors amongst older individuals in linked electronic health records: An assessment in a population based study

PubMed Central

van Hoek, Albert J.; Walker, Jemma L.; Mathur, Rohini; Smeeth, Liam; Thomas, Sara L.

2017-01-01

Identification and quantification of health inequities amongst specific social groups is a pre-requisite for designing targeted healthcare interventions. This study investigated the recording of social factors in linked electronic health records (EHR) of individuals aged ≥65 years, to assess the potential of these data to identify the social determinants of disease burden and uptake of healthcare interventions. Methodology was developed for ascertaining social factors recorded on or before a pre-specified index date (01/01/2013) using primary care data from Clinical Practice Research Datalink (CPRD) linked to hospitalisation and deprivation data in a cross-sectional study. Social factors included: religion, ethnicity, immigration status, small area-level deprivation, place of residence (including communal establishments such as care homes), marital status and living arrangements (e.g. living alone, cohabitation). Each social factor was examined for: completeness of recording including improvements in completeness by using other linked EHR, timeliness of recording for factors that might change over time and their representativeness (compared with English 2011 Census data when available). Data for 591,037 individuals from 389 practices from England were analysed. The completeness of recording varied from 1.6% for immigration status to ~80% for ethnicity. Linkages provided the deprivation data (available for 82% individuals) and improved completeness of ethnicity recording from 55% to 79% (when hospitalisation data were added). Data for ethnicity, deprivation, living arrangements and care home residence were comparable to the Census data. For time-varying variables such as residence and living alone, ~60% and ~35% respectively of those with available data, had this information recorded within the last 5 years of the index date. This work provides methods to identify social factors in EHR relevant to older individuals and shows that factors such as ethnicity

Working memory dysfunctions predict social problem solving skills in schizophrenia.

PubMed

Huang, Jia; Tan, Shu-ping; Walsh, Sarah C; Spriggens, Lauren K; Neumann, David L; Shum, David H K; Chan, Raymond C K

2014-12-15

The current study aimed to examine the contribution of neurocognition and social cognition to components of social problem solving. Sixty-seven inpatients with schizophrenia and 31 healthy controls were administrated batteries of neurocognitive tests, emotion perception tests, and the Chinese Assessment of Interpersonal Problem Solving Skills (CAIPSS). MANOVAs were conducted to investigate the domains in which patients with schizophrenia showed impairments. Correlations were used to determine which impaired domains were associated with social problem solving, and multiple regression analyses were conducted to compare the relative contribution of neurocognitive and social cognitive functioning to components of social problem solving. Compared with healthy controls, patients with schizophrenia performed significantly worse in sustained attention, working memory, negative emotion, intention identification and all components of the CAIPSS. Specifically, sustained attention, working memory and negative emotion identification were found to correlate with social problem solving and 1-back accuracy significantly predicted the poor performance in social problem solving. Among the dysfunctions in schizophrenia, working memory contributed most to deficits in social problem solving in patients with schizophrenia. This finding provides support for targeting working memory in the development of future social problem solving rehabilitation interventions. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Mothers' depressive symptoms and children's cognitive and social agency: Predicting first-grade cognitive functioning.

PubMed

Yan, Ni; Dix, Theodore

2016-08-01

Using data from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (N = 1,364), the present study supports an agentic perspective; it demonstrates that mothers' depressive symptoms in infancy predict children's poor first-grade cognitive functioning because depressive symptoms predict children's low social and cognitive agency-low motivation to initiate social interaction and actively engage in activities. When mothers' depressive symptoms were high in infancy, children displayed poor first-grade cognitive functioning due to (a) tendencies to become socially withdrawn by 36 months and low in mastery motivation by 54 months and (b) tendencies for children's low agency to predict declines in mothers' sensitivity and cognitive stimulation. Findings suggest that mothers' depressive symptoms undermine cognitive development through bidirectional processes centered on children's low motivation to engage in social interaction and initiate and persist at everyday tasks. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Linking Contextual Affordances: Examining Racial-Ethnic Socialization and Parental Career Support among African American College Students

ERIC Educational Resources Information Center

Blackmon, Sha'Kema M.; Thomas, Anita Jones

2014-01-01

This exploratory investigation examined the link between self-reported racial-ethnic socialization experiences and perceived parental career support among African American undergraduate and graduate students. The results of two separate multivariate multiple regression analyses found that messages about coping with racism positively predicted…

Using Social Cognitive Theory to Predict Physical Activity and Fitness in Underserved Middle School Children

ERIC Educational Resources Information Center

Martin, Jeffrey J.; McCaughtry, Nate; Flory, Sara; Murphy, Anne; Wisdom, Kimberlydawn

2011-01-01

Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to predict PA and fitness in middle school children (N = 506, ages 10-14 years). Using…

Culture shapes whether the pursuit of happiness predicts higher or lower well-being.

PubMed

Ford, Brett Q; Dmitrieva, Julia O; Heller, Daniel; Chentsova-Dutton, Yulia; Grossmann, Igor; Tamir, Maya; Uchida, Yukiko; Koopmann-Holm, Birgit; Floerke, Victoria A; Uhrig, Meike; Bokhan, Tatiana; Mauss, Iris B

2015-12-01

Pursuing happiness can paradoxically impair well-being. Here, the authors propose the potential downsides to pursuing happiness may be specific to individualistic cultures. In collectivistic (vs. individualistic) cultures, pursuing happiness may be more successful because happiness is viewed--and thus pursued--in relatively socially engaged ways. In 4 geographical regions that vary in level of collectivism (United States, Germany, Russia, East Asia), we assessed participants' well-being, motivation to pursue happiness, and to what extent they pursued happiness in socially engaged ways. Motivation to pursue happiness predicted lower well-being in the United States, did not predict well-being in Germany, and predicted higher well-being in Russia and in East Asia. These cultural differences in the link between motivation to pursue happiness and well-being were explained by cultural differences in the socially engaged pursuit of happiness. These findings suggest that culture shapes whether the pursuit of happiness is linked with better or worse well-being, perhaps via how people pursue happiness. (c) 2015 APA, all rights reserved).

A multi-label, semi-supervised classification approach applied to personality prediction in social media.

PubMed

Lima, Ana Carolina E S; de Castro, Leandro Nunes

2014-10-01

Social media allow web users to create and share content pertaining to different subjects, exposing their activities, opinions, feelings and thoughts. In this context, online social media has attracted the interest of data scientists seeking to understand behaviours and trends, whilst collecting statistics for social sites. One potential application for these data is personality prediction, which aims to understand a user's behaviour within social media. Traditional personality prediction relies on users' profiles, their status updates, the messages they post, etc. Here, a personality prediction system for social media data is introduced that differs from most approaches in the literature, in that it works with groups of texts, instead of single texts, and does not take users' profiles into account. Also, the proposed approach extracts meta-attributes from texts and does not work directly with the content of the messages. The set of possible personality traits is taken from the Big Five model and allows the problem to be characterised as a multi-label classification task. The problem is then transformed into a set of five binary classification problems and solved by means of a semi-supervised learning approach, due to the difficulty in annotating the massive amounts of data generated in social media. In our implementation, the proposed system was trained with three well-known machine-learning algorithms, namely a Naïve Bayes classifier, a Support Vector Machine, and a Multilayer Perceptron neural network. The system was applied to predict the personality of Tweets taken from three datasets available in the literature, and resulted in an approximately 83% accurate prediction, with some of the personality traits presenting better individual classification rates than others. Copyright © 2014 Elsevier Ltd. All rights reserved.

The roles of low literacy and social support in predicting the preventability of hospital admission.

PubMed

Arozullah, Ahsan M; Lee, Shoou-Yih D; Khan, Taha; Kurup, Sindhu; Ryan, Jeffrey; Bonner, Michael; Soltysik, Robert; Yarnold, Paul R

2006-02-01

Prior studies found higher hospitalization rates among patients with low literacy, but did not determine the preventability of these admissions or consider other determinants of hospitalization, such as social support. This study evaluated whether low literacy was a predictor for preventability of hospitalization when considered in the context of social support, sociodemographics, health status, and risk behaviors. A convenience sample of 400 patients, admitted to general medicine wards in a university-affiliated Veterans Affairs hospital between August 1, 2001 and April 1, 2003, completed a face-to-face interview to assess literacy, sociodemographics, social support, health status, and risk behaviors. Two Board-certified Internists independently assessed preventability of hospitalization and determined the primary preventable cause through blinded medical chart reviews. Neither low literacy (social support for medical care (P<.04), < or =3 annual clinic visits (P<.005), and > or =12 people talked to weekly (P<.023). Among nonbinge drinkers with lower social support for medical care, larger social networks were predictive of preventability of hospitalization. Among nonbinge drinkers with higher support for medical care, lower outpatient utilization was predictive of the preventability of hospitalization. While low literacy was not predictive of admission preventability, the formal assessment of alcohol binge drinking, social support for medical care, social network size, and prior outpatient utilization may enhance our ability to predict the preventability of hospitalizations and develop targeted interventions.

Anticipatory smiling: Linking early affective communication and social outcome

PubMed Central

Parlade, Meaghan Venezia; Messinger, Daniel S.; Delgado, Christine E.F.; Kaiser, Marygrace Yale; Van Hecke, Amy Vaughan; Mundy, Peter C.

2009-01-01

In anticipatory smiles, infants appear to communicate pre-existing positive affect by smiling at an object and then turning the smile toward an adult. We report two studies in which the precursors, development, and consequences of anticipatory smiling were investigated. Study 1 revealed a positive correlation between infant smiling at 6 months and the level of anticipatory smiling at 8 and 10 months during joint attention episodes, as well as a positive correlation between anticipatory smiling and parent-rated social expressivity scores at 30 months. Study 2 confirmed a developmental increase in the number of infants using anticipatory smiles between 9 and 12 months that had been initially documented in the Study 1 sample [Venezia, M., Messinger, D. S., Thorp, D., & Mundy, P. (2004). The development of anticipatory smiling. Infancy, 6(3), 397–406]. Additionally, anticipatory smiling at 9 months positively predicted parent-rated social competence scores at 30 months. Findings are discussed with regard to the importance of anticipatory smiling in early socioemotional development. PMID:19004500

On the Prediction of Flickr Image Popularity by Analyzing Heterogeneous Social Sensory Data.

PubMed

Aloufi, Samah; Zhu, Shiai; El Saddik, Abdulmotaleb

2017-03-19

The increase in the popularity of social media has shattered the gap between the physical and virtual worlds. The content generated by people or social sensors on social media provides information about users and their living surroundings, which allows us to access a user's preferences, opinions, and interactions. This provides an opportunity for us to understand human behavior and enhance the services provided for both the real and virtual worlds. In this paper, we will focus on the popularity prediction of social images on Flickr, a popular social photo-sharing site, and promote the research on utilizing social sensory data in the context of assisting people to improve their life on the Web. Social data are different from the data collected from physical sensors; in the fact that they exhibit special characteristics that pose new challenges. In addition to their huge quantity, social data are noisy, unstructured, and heterogeneous. Moreover, they involve human semantics and contextual data that require analysis and interpretation based on human behavior. Accordingly, we address the problem of popularity prediction for an image by exploiting three main factors that are important for making an image popular. In particular, we investigate the impact of the image's visual content, where the semantic and sentiment information extracted from the image show an impact on its popularity, as well as the textual information associated with the image, which has a fundamental role in boosting the visibility of the image in the keyword search results. Additionally, we explore social context, such as an image owner's popularity and how it positively influences the image popularity. With a comprehensive study on the effect of the three aspects, we further propose to jointly consider the heterogeneous social sensory data. Experimental results obtained from real-world data demonstrate that the three factors utilized complement each other in obtaining promising results in the

On the Prediction of Flickr Image Popularity by Analyzing Heterogeneous Social Sensory Data

PubMed Central

Aloufi, Samah; Zhu, Shiai; El Saddik, Abdulmotaleb

2017-01-01

The increase in the popularity of social media has shattered the gap between the physical and virtual worlds. The content generated by people or social sensors on social media provides information about users and their living surroundings, which allows us to access a user’s preferences, opinions, and interactions. This provides an opportunity for us to understand human behavior and enhance the services provided for both the real and virtual worlds. In this paper, we will focus on the popularity prediction of social images on Flickr, a popular social photo-sharing site, and promote the research on utilizing social sensory data in the context of assisting people to improve their life on the Web. Social data are different from the data collected from physical sensors; in the fact that they exhibit special characteristics that pose new challenges. In addition to their huge quantity, social data are noisy, unstructured, and heterogeneous. Moreover, they involve human semantics and contextual data that require analysis and interpretation based on human behavior. Accordingly, we address the problem of popularity prediction for an image by exploiting three main factors that are important for making an image popular. In particular, we investigate the impact of the image’s visual content, where the semantic and sentiment information extracted from the image show an impact on its popularity, as well as the textual information associated with the image, which has a fundamental role in boosting the visibility of the image in the keyword search results. Additionally, we explore social context, such as an image owner’s popularity and how it positively influences the image popularity. With a comprehensive study on the effect of the three aspects, we further propose to jointly consider the heterogeneous social sensory data. Experimental results obtained from real-world data demonstrate that the three factors utilized complement each other in obtaining promising results in the

Anticipating Their Future: Adolescent Values for the Future Predict Adult Behaviors

PubMed Central

Finlay, Andrea; Wray-Lake, Laura; Warren, Michael; Maggs, Jennifer L.

2014-01-01

Adolescent future values – beliefs about what will matter to them in the future – may shape their adult behavior. Utilizing a national longitudinal British sample, this study examined whether adolescent future values in six domains (i.e., family responsibility, full-time job, personal responsibility, autonomy, civic responsibility, and hedonistic privilege) predicted adult social roles, civic behaviors, and alcohol use. Future values positively predicted behaviors within the same domain; fewer cross-domain associations were evident. Civic responsibility positively predicted adult civic behaviors, but negatively predicted having children. Hedonistic privilege positively predicted adult alcohol use and negatively predicted civic behaviors. Results suggest that attention should be paid to how adolescents are thinking about their futures due to the associated links with long-term social and health behaviors. PMID:26279595

Linking functional diversity and social actor strategies in a framework for interdisciplinary analysis of nature's benefits to society

PubMed Central

Díaz, Sandra; Cáceres, Daniel M.; Trainor, Sarah F.; Pérez-Harguindeguy, Natalia; Bret-Harte, M. Syndonia; Finegan, Bryan; Peña-Claros, Marielos; Poorter, Lourens

2011-01-01

The crucial role of biodiversity in the links between ecosystems and societies has been repeatedly highlighted both as source of wellbeing and as a target of human actions, but not all aspects of biodiversity are equally important to different ecosystem services. Similarly, different social actors have different perceptions of and access to ecosystem services, and therefore, they have different wants and capacities to select directly or indirectly for particular biodiversity and ecosystem characteristics. Their choices feed back onto the ecosystem services provided to all parties involved and in turn, affect future decisions. Despite this recognition, the research communities addressing biodiversity, ecosystem services, and human outcomes have yet to develop frameworks that adequately treat the multiple dimensions and interactions in the relationship. Here, we present an interdisciplinary framework for the analysis of relationships between functional diversity, ecosystem services, and human actions that is applicable to specific social environmental systems at local scales. We connect the mechanistic understanding of the ecological role of diversity with its social relevance: ecosystem services. The framework permits connections between functional diversity components and priorities of social actors using land use decisions and ecosystem services as the main links between these ecological and social components. We propose a matrix-based method that provides a transparent and flexible platform for quantifying and integrating social and ecological information and negotiating potentially conflicting land uses among multiple social actors. We illustrate the applicability of our framework by way of land use examples from temperate to subtropical South America, an area of rapid social and ecological change. PMID:21220325

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

Fearfulness moderates the link between childhood social withdrawal and adolescent reward response

PubMed Central

Shaw, Daniel S.; Forbes, Erika E.

2015-01-01

Withdrawal from peers during childhood may reflect disruptions in reward functioning that heighten vulnerability to affective disorders during adolescence. The association between socially withdrawn behavior and reward functioning may depend on traits that influence this withdrawal, such as fearfulness or unsociability. In a study of 129 boys, we evaluated how boys’ fearfulness and sociability at age 5 and social withdrawal at school at ages 6 to 10 and during a summer camp at age 9/10 were associated with their neural response to reward at age 20. Greater social withdrawal during childhood was associated with heightened striatal and mPFC activation when anticipating rewards at age 20. Fearfulness moderated this effect to indicate that social withdrawal was associated with heightened reward-related response in the striatum for boys high on fearfulness. Altered striatal response associated with social withdrawal and fearfulness predicted greater likelihood to have a lifetime history of depression and social phobia at age 20. These findings add greater specificity to previous findings that children high in traits related to fear of novelty show altered reward responses, by identifying fearfulness (but not low levels of sociability) as a potential underlying mechanism that contributes to reward alterations in withdrawn children. PMID:25193948

Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact

PubMed Central

2011-01-01

Background Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known. Objective (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles. Methods Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. Results A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant

Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact.

PubMed

Eysenbach, Gunther

2011-12-19

Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known. (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles. Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain

Social interaction anxiety and personality traits predicting engagement in health risk sexual behaviors.

PubMed

Rahm-Knigge, Ryan L; Prince, Mark A; Conner, Bradley T

2018-06-01

Individuals with social interaction anxiety, a facet of social anxiety disorder, withdraw from or avoid social encounters and generally avoid risks. However, a subset engages in health risk sexual behavior (HRSB). Because sensation seeking, emotion dysregulation, and impulsivity predict engagement in HRSB among adolescents and young adults, the present study hypothesized that latent classes of social interaction anxiety and these personality traits would differentially predict likelihood of engagement in HRSB. Finite mixture modeling was used to discern four classes: two low social interaction anxiety classes distinguished by facets of emotion dysregulation, positive urgency, and negative urgency (Low SIAS High Urgency and Low SIAS Low Urgency) and two high social interaction anxiety classes distinguished by positive urgency, negative urgency, risk seeking, and facets of emotion dysregulation (High SIAS High Urgency and High SIAS Low Urgency). HRSB were entered into the model as auxiliary distal outcomes. Of importance to this study were findings that the High SIAS High Urgency class was more likely to engage in most identified HRSB than the High SIAS Low Urgency class. This study extends previous findings on the heterogeneity of social interaction anxiety by identifying the effects of social interaction anxiety and personality on engagement in HRSB. Copyright © 2018 Elsevier Ltd. All rights reserved.

Infants, mothers, and dyadic contributions to stability and prediction of social stress response at 6 months.

PubMed

Provenzi, Livio; Olson, Karen L; Montirosso, Rosario; Tronick, Ed

2016-01-01

The study of infants' interactive style and social stress response to repeated stress exposures is of great interest for developmental and clinical psychologists. Stable maternal and dyadic behavior is critical to sustain infants' development of an adaptive social stress response, but the association between infants' interactive style and social stress response has received scant attention in previous literature. In the present article, overtime stability of infant, maternal, and dyadic behaviors was measured across 2 social stress (i.e., Face-to-Face Still-Face, FFSF) exposures, separated by 15 days. Moreover, infant, maternal, and dyadic behaviors were simultaneously assessed as predictors of infants' social stress to both FFSF exposures. Eighty-one mother-infant dyads underwent the FFSF twice, at 6 months (Exposure 1: the first social stress) and at 6 months and 15 days (Exposure 2: repeated social stress). Infant and mother behavior and dyadic synchrony were microanalytically coded. Overall, individual behavioral stability emerged between FFSF exposures. Infants' response to the first stress was predicted by infant behavior during Exposure 1 Play. Infants' response to the repeated social stress was predicted by infants' response to the first exposure to the Still-Face and by infants' behavior and dyadic synchrony during Exposure 2 Play. Findings reveal stability for individual, but not for dyadic, behavior between 2 social stress exposures at 6 months. Infants' response to repeated social stress was predicted by infants' earlier stress response, infants' own behavior in play, and dyadic synchrony. No predictive effects of maternal behavior were found. Insights for research and clinical work are discussed. (c) 2015 APA, all rights reserved).

Mediation effect of beliefs about pleasure and emotional experience between social anhedonia and prediction of pleasant events.

PubMed

Hu, Hui-Xin; Chu, Min-Yi; Yang, Yin; Wang, Ling-Ling; Zhang, Rui-Ting; Lui, Simon S Y; Cheung, Eric F C; Chan, Raymond C K

2018-06-01

Few studies have examined whether there is a relationship between social anhedonia and prediction of future events and the role of beliefs about pleasure and emotional experience. In this study, 513 college students were recruited to complete a set of self-reported questionnaires, including the Revised Social Anhedonia Scale (CSAS), the Temporal Experience of Pleasure Scale (TEPS), the Belief about Pleasure Scale (BAPS) and the Beck Depression Inventory. Moreover, a checklist of 100 daily life events was also administrated to all participants. Mediation analysis found that social anhedonia had a direct impact on prediction of pleasant events. Emotional experience partly mediated the relationship between social anhedonia and subjective prediction of pleasant events. However, beliefs about pleasure had no significant mediation effect between social anhedonia and prediction of pleasant events, but were shown to influence the subjective prediction of pleasant events completely through emotional experience. These findings suggest that beliefs about pleasure and emotional experience may be considered promising factors for interventions in individuals with anhedonia. Copyright © 2018. Published by Elsevier B.V.

Linking academic social environments, ego-identity formation, ego virtues, and academic success.

PubMed

Good, Marie; Adams, Gerald R

2008-01-01

This study used Structural Equation Modeling to test an Eriksonian conceptual model linking academic social environments (relationships with faculty and fellow students), ego-identity formation, ego virtues, and academic success. Participants included 765 first-year students at a university in southern Ontario, Canada. Results indicated that supportive relationships with faculty was directly related to higher average grades and perceived academic ability, whereas positive relationships with fellow students was indirectly related to academic success through ego virtues. Positive ego-identity formation (identity achievement) was also indirectly related to academic success through ego virtues.

Link Scheduling Algorithm with Interference Prediction for Multiple Mobile WBANs

PubMed Central

Le, Thien T. T.

2017-01-01

As wireless body area networks (WBANs) become a key element in electronic healthcare (e-healthcare) systems, the coexistence of multiple mobile WBANs is becoming an issue. The network performance is negatively affected by the unpredictable movement of the human body. In such an environment, inter-WBAN interference can be caused by the overlapping transmission range of nearby WBANs. We propose a link scheduling algorithm with interference prediction (LSIP) for multiple mobile WBANs, which allows multiple mobile WBANs to transmit at the same time without causing inter-WBAN interference. In the LSIP, a superframe includes the contention access phase using carrier sense multiple access with collision avoidance (CSMA/CA) and the scheduled phase using time division multiple access (TDMA) for non-interfering nodes and interfering nodes, respectively. For interference prediction, we define a parameter called interference duration as the duration during which disparate WBANs interfere with each other. The Bayesian model is used to estimate and classify the interference using a signal to interference plus noise ratio (SINR) and the number of neighboring WBANs. The simulation results show that the proposed LSIP algorithm improves the packet delivery ratio and throughput significantly with acceptable delay. PMID:28956827

Multivariate Brain Prediction of Heart Rate and Skin Conductance Responses to Social Threat.

PubMed

Eisenbarth, Hedwig; Chang, Luke J; Wager, Tor D

2016-11-23

Psychosocial stressors induce autonomic nervous system (ANS) responses in multiple body systems that are linked to health risks. Much work has focused on the common effects of stress, but ANS responses in different body systems are dissociable and may result from distinct patterns of cortical-subcortical interactions. Here, we used machine learning to develop multivariate patterns of fMRI activity predictive of heart rate (HR) and skin conductance level (SCL) responses during social threat in humans (N = 18). Overall, brain patterns predicted both HR and SCL in cross-validated analyses successfully (r HR = 0.54, r SCL = 0.58, both p < 0.0001). These patterns partly reflected central stress mechanisms common to both responses because each pattern predicted the other signal to some degree (r HR→SCL = 0.21 and r SCL→HR = 0.22, both p < 0.01), but they were largely physiological response specific. Both patterns included positive predictive weights in dorsal anterior cingulate and cerebellum and negative weights in ventromedial PFC and local pattern similarity analyses within these regions suggested that they encode common central stress mechanisms. However, the predictive maps and searchlight analysis suggested that the patterns predictive of HR and SCL were substantially different across most of the brain, including significant differences in ventromedial PFC, insula, lateral PFC, pre-SMA, and dmPFC. Overall, the results indicate that specific patterns of cerebral activity track threat-induced autonomic responses in specific body systems. Physiological measures of threat are not interchangeable, but rather reflect specific interactions among brain systems. We show that threat-induced increases in heart rate and skin conductance share some common representations in the brain, located mainly in the vmPFC, temporal and parahippocampal cortices, thalamus, and brainstem. However, despite these similarities, the brain patterns that predict these two autonomic responses

Link prediction boosted psychiatry disorder classification for functional connectivity network

NASA Astrophysics Data System (ADS)

Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

2017-02-01

Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

An interpersonal circumplex model of children's social goals: links with peer-reported behavior and sociometric status.

PubMed

Ojanen, Tiina; Grönroos, Matti; Salmivalli, Christina

2005-09-01

The objective of the present research was to develop an assessment model for children's social goals. The aims were (a) to fit children's social goals to a circumplex model and to examine links between goals and peer-reported social behaviors (aggression, withdrawal, and prosocial behavior) in a sample of 276 participants (134 girls, 11- to 12-year-olds) and (b) to replicate these findings and examine whether social behavior mediates the relationship between goals and sociometric status in an independent cross-validation sample of 310 participants (143 girls, 11- to 13-year-olds). Results showed a satisfactory fit to the circumplex model and adequate psychometric properties of the goal scales of the new measure, the Interpersonal Goals Inventory for Children. Other findings included significant and meaningful relations between goals and peer-reported behavior. Social behavior mediated the relations between goals and sociometric status. Copyright 2005 APA, all rights reserved.

Predicting the Retention Behavior of Specific O-Linked Glycopeptides.

PubMed

Badgett, Majors J; Boyes, Barry; Orlando, Ron

2017-09-01

O -Linked glycosylation is a common post-translational modification that can alter the overall structure, polarity, and function of proteins. Reverse-phase (RP) chromatography is the most common chromatographic approach to analyze O -glycosylated peptides and their unmodified counterparts, even though this approach often does not provide adequate separation of these two species. Hydrophilic interaction liquid chromatography (HILIC) can be a solution to this problem, as the polar glycan interacts with the polar stationary phase and potentially offers the ability to resolve the peptide from its modified form(s). In this paper, HILIC is used to separate peptides with O - N -acetylgalactosamine ( O -GalNAc), O - N -acetylglucosamine ( O -GlcNAc), and O -fucose additions from their native forms, and coefficients representing the extent of hydrophilicity were derived using linear regression analysis as a means to predict the retention times of peptides with these modifications.

Predicting the Retention Behavior of Specific O-Linked Glycopeptides

PubMed Central

Badgett, Majors J.; Boyes, Barry; Orlando, Ron

2017-01-01

O-Linked glycosylation is a common post-translational modification that can alter the overall structure, polarity, and function of proteins. Reverse-phase (RP) chromatography is the most common chromatographic approach to analyze O-glycosylated peptides and their unmodified counterparts, even though this approach often does not provide adequate separation of these two species. Hydrophilic interaction liquid chromatography (HILIC) can be a solution to this problem, as the polar glycan interacts with the polar stationary phase and potentially offers the ability to resolve the peptide from its modified form(s). In this paper, HILIC is used to separate peptides with O-N-acetylgalactosamine (O-GalNAc), O-N-acetylglucosamine (O-GlcNAc), and O-fucose additions from their native forms, and coefficients representing the extent of hydrophilicity were derived using linear regression analysis as a means to predict the retention times of peptides with these modifications. PMID:28785176

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.

Epidemics in Adaptive Social Networks with Temporary Link Deactivation

NASA Astrophysics Data System (ADS)

Tunc, Ilker; Shkarayev, Maxim S.; Shaw, Leah B.

2013-04-01

Disease spread in a society depends on the topology of the network of social contacts. Moreover, individuals may respond to the epidemic by adapting their contacts to reduce the risk of infection, thus changing the network structure and affecting future disease spread. We propose an adaptation mechanism where healthy individuals may choose to temporarily deactivate their contacts with sick individuals, allowing reactivation once both individuals are healthy. We develop a mean-field description of this system and find two distinct regimes: slow network dynamics, where the adaptation mechanism simply reduces the effective number of contacts per individual, and fast network dynamics, where more efficient adaptation reduces the spread of disease by targeting dangerous connections. Analysis of the bifurcation structure is supported by numerical simulations of disease spread on an adaptive network. The system displays a single parameter-dependent stable steady state and non-monotonic dependence of connectivity on link deactivation rate.

Human hypocretin and melanin-concentrating hormone levels are linked to emotion and social interaction.

PubMed

Blouin, Ashley M; Fried, Itzhak; Wilson, Charles L; Staba, Richard J; Behnke, Eric J; Lam, Hoa A; Maidment, Nigel T; Karlsson, Karl Æ; Lapierre, Jennifer L; Siegel, Jerome M

2013-01-01

The neurochemical changes underlying human emotions and social behaviour are largely unknown. Here we report on the changes in the levels of two hypothalamic neuropeptides, hypocretin-1 and melanin-concentrating hormone, measured in the human amygdala. We show that hypocretin-1 levels are maximal during positive emotion, social interaction and anger, behaviours that induce cataplexy in human narcoleptics. In contrast, melanin-concentrating hormone levels are minimal during social interaction, but are increased after eating. Both peptides are at minimal levels during periods of postoperative pain despite high levels of arousal. Melanin-concentrating hormone levels increase at sleep onset, consistent with a role in sleep induction, whereas hypocretin-1 levels increase at wake onset, consistent with a role in wake induction. Levels of these two peptides in humans are not simply linked to arousal, but rather to specific emotions and state transitions. Other arousal systems may be similarly emotionally specialized.

Using Social Identity to Explore the Link between a Decline in Adolescent Smoking and an Increase in Mobile Phone Use

ERIC Educational Resources Information Center

Cassidy, Simon

2006-01-01

Purpose--The study seeks to further explore the hypothesised link between the increase in mobile phone ownership and use and the reported decline in adolescent smoking. Evidence for the link was gathered by examining perceptions of mobile phone use in the context of social identity and adolescent smoking. Design/methodology/approach--The study…

Low Social Status Markers: Do They Predict Depressive Symptoms in Adolescence?

PubMed

Jackson, Benita; Goodman, Elizabeth

2011-07-01

Some markers of social disadvantage are associated robustly with depressive symptoms among adolescents: female gender and lower socioeconomic status (SES), respectively. Others are associated equivocally, notably Black v. White race/ethnicity. Few studies examine whether markers of social disadvantage by gender, SES, and race/ethnicity jointly predict self-reported depressive symptoms during adolescence; this was our goal. Secondary analyses were conducted on data from a socioeconomically diverse community-based cohort study of non-Hispanic Black and White adolescents (N = 1,263, 50.4% female). Multivariable general linear models tested if female gender, Black race/ethnicity, and lower SES (assessed by parent education and household income), and their interactions predicted greater depressive symptoms reported on the Center for Epidemiological Studies-Depression scale. Models adjusted for age and pubertal status. Univariate analyses revealed more depressive symptoms in females, Blacks, and participants with lower SES. Multivariable models showed females across both racial/ethnic groups reported greater depressive symptoms; Blacks demonstrated more depressive symptoms than did Whites but when SES was included this association disappeared. Exploratory analyses suggested Blacks gained less mental health benefit from increased SES. However there were no statistically significant interactions among gender, race/ethnicity, or SES. Taken together, we conclude that complex patterning among low social status domains within gender, race/ethnicity, and SES predicts depressive symptoms among adolescents.

Individuals' quality of life linked to major life events, perceived social support, and personality traits.

PubMed

Pocnet, Cornelia; Antonietti, Jean-Philippe; Strippoli, Marie-Pierre F; Glaus, Jennifer; Preisig, Martin; Rossier, Jérôme

2016-11-01

The aim of this study was to investigate the relationship between major recent life events that occurred during the last 5 years, social and personal resources, and subjective quality of life (QoL). A total of 1801 participants from the general population (CoLaus/PsyCoLaus study) completed the Life Events Questionnaire, the Social Support Questionnaire, the NEO Five-Factor Inventory Revised, and the Manchester Short Assessment of Quality of Life. Major life events were modestly associated with the QoL (about 5 % of the explained variance). However, QoL was significantly related to perceived social support and personality traits (about 37 % of the explained variance). Particularly, perceived social support, extraversion and conscientiousness personality dimensions were positively linked to life satisfaction, whereas a high level of neuroticism was negatively associated with QoL. This study highlights the negative but temporary association between critical events and QoL. However, a combination of high conscientiousness and extraversion, and positive social support may explain better variances for a high-perceived QoL.

Prediction-error in the context of real social relationships modulates reward system activity.

PubMed

Poore, Joshua C; Pfeifer, Jennifer H; Berkman, Elliot T; Inagaki, Tristen K; Welborn, Benjamin L; Lieberman, Matthew D

2012-01-01

The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward-social validation-and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

Can infants' orientation to social stimuli predict later joint attention skills?

PubMed

Schietecatte, Inge; Roeyers, Herbert; Warreyn, Petra

2012-06-01

From the moment infants are born, they seem to prefer orienting to social stimuli, over objects and non-social stimuli. This preference lasts throughout adulthood and is believed to play a crucial role in social-communicative development. By following up a group of infants at the age of 6, 8, and 12 months, this study explored the role of social orienting in the early development of joint attention skills. The expected association between social orienting and joint attention was partially confirmed. Social orienting in real-life photographs of everyday situations was not related to later joint attention skills, however fixation to the eyes in a neutral face was related to response to joint attention skills, and fixation to the eyes in a dynamic video clip of a talking person was predictive of initiating joint attention skills. Several alternative interpretations of the results are discussed. ©2011 The British Psychological Society.

Predicting and influencing voice therapy adherence using social-cognitive factors and mobile video.

PubMed

van Leer, Eva; Connor, Nadine P

2015-05-01

Patient adherence to voice therapy is an established challenge. The purpose of this study was (a) to examine whether adherence to treatment could be predicted from three social-cognitive factors measured at treatment onset: self-efficacy, goal commitment, and the therapeutic alliance, and (b) to test whether the provision of clinician, self-, and peer model mobile treatment videos on MP4 players would influence the same triad of social cognitive factors and the adherence behavior of patients. Forty adults with adducted hyperfunction with and without benign lesions were prospectively randomized to either 4 sessions of voice therapy enhanced by MP4 support or without MP4 support. Adherence between sessions was assessed through self-report. Social cognitive factors and voice outcomes were assessed at the beginning and end of therapy. Utility of MP4 support was assessed via interviews. Self-efficacy and the therapeutic alliance predicted a significant amount of adherence variance. MP4 support significantly increased generalization, self-efficacy for generalization, and the therapeutic alliance. An interaction effect demonstrated that MP4 support was particularly effective for patients who started therapy with poor self-efficacy for generalization. Adherence may be predicted and influenced via social-cognitive means. Mobile technology can extend therapy to extraclinical settings.

Fearfulness moderates the link between childhood social withdrawal and adolescent reward response.

PubMed

Morgan, Judith K; Shaw, Daniel S; Forbes, Erika E

2015-06-01

Withdrawal from peers during childhood may reflect disruptions in reward functioning that heighten vulnerability to affective disorders during adolescence. The association between socially withdrawn behavior and reward functioning may depend on traits that influence this withdrawal, such as fearfulness or unsociability. In a study of 129 boys, we evaluated how boys' fearfulness and sociability at age 5 and social withdrawal at school at ages 6 to 10 and during a summer camp at age 9/10 were associated with their neural response to reward at age 20. Greater social withdrawal during childhood was associated with heightened striatal and mPFC activation when anticipating rewards at age 20. Fearfulness moderated this effect to indicate that social withdrawal was associated with heightened reward-related response in the striatum for boys high on fearfulness. Altered striatal response associated with social withdrawal and fearfulness predicted greater likelihood to have a lifetime history of depression and social phobia at age 20. These findings add greater specificity to previous findings that children high in traits related to fear of novelty show altered reward responses, by identifying fearfulness (but not low levels of sociability) as a potential underlying mechanism that contributes to reward alterations in withdrawn children. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Self-reference and predictive, normative and prescriptive approaches in applications of systems thinking in social sciences—(Survey)

NASA Astrophysics Data System (ADS)

Mesjasz, Czesław

2000-05-01

Cybernetics, systems thinking or systems theory, have been viewed as instruments of enhancing predictive, normative and prescriptive capabilities of the social sciences, beginning from microscale-management and ending with various reference to the global system. Descriptions, explanations and predictions achieved thanks to various systems ideas were also viewed as supportive for potential governance of social phenomena. The main aim of the paper is to examine what could be the possible applications of modern systems thinking in predictive, normative and prescriptive approaches in modern social sciences, beginning from management theory and ending with global studies. Attention is paid not only to "classical" mathematical systems models but also to the role of predictive, normative and prescriptive interpretations of analogies and metaphors associated with application of the classical ("first order cybernetics") and modern ("second order cybernetics", "complexity theory") systems thinking in social sciences.

Correlations between Community Structure and Link Formation in Complex Networks

PubMed Central

Liu, Zhen; He, Jia-Lin; Kapoor, Komal; Srivastava, Jaideep

2013-01-01

Background Links in complex networks commonly represent specific ties between pairs of nodes, such as protein-protein interactions in biological networks or friendships in social networks. However, understanding the mechanism of link formation in complex networks is a long standing challenge for network analysis and data mining. Methodology/Principal Findings Links in complex networks have a tendency to cluster locally and form so-called communities. This widely existed phenomenon reflects some underlying mechanism of link formation. To study the correlations between community structure and link formation, we present a general computational framework including a theory for network partitioning and link probability estimation. Our approach enables us to accurately identify missing links in partially observed networks in an efficient way. The links having high connection likelihoods in the communities reveal that links are formed preferentially to create cliques and accordingly promote the clustering level of the communities. The experimental results verify that such a mechanism can be well captured by our approach. Conclusions/Significance Our findings provide a new insight into understanding how links are created in the communities. The computational framework opens a wide range of possibilities to develop new approaches and applications, such as community detection and missing link prediction. PMID:24039818

When performance-approach goals predict academic achievement and when they do not: a social value approach.

PubMed

Dompnier, Benoît; Darnon, Céline; Butera, Fabrizio

2013-09-01

Research on achievement goal promotion at University has shown that performance-approach goals are perceived as a means to succeed at University (high social utility) but are not appreciated (low social desirability). We argue that such a paradox could explain why research has detected that performance-approach goals consistently predict academic grades. First-year psychology students answered a performance-approach goal scale with standard, social desirability and social utility instructions. Participants' grades were recorded at the end of the semester. Results showed that the relationship between performance-approach goals and grades was inhibited by the increase of these goals' social desirability and facilitated by the increase of their social utility, revealing that the predictive validity of performance-approach goals depends on social value. © 2013 The British Psychological Society.

Links between Parent-Teacher Relationships and Kindergartners' Social Skills: Do Child Ethnicity and Family Income Matter?

ERIC Educational Resources Information Center

Iruka, Iheoma U.; Winn, Donna-Marie C.; Kingsley, Susan J.; Orthodoxou, Yannick J.

2011-01-01

This study uses National Center for Early Development and Learning (NCEDL) data to examine the moderating effects of child ethnicity and family income on the links between parent-teacher relationships and kindergartners' social skills. This study includes 481 Caucasian, African American, and Latino children from low-income households. Overall,…

Linking Affective Commitment, Career Self-Efficacy, and Outcome Expectations: A Test of Social Cognitive Career Theory

ERIC Educational Resources Information Center

Conklin, Amanda M.; Dahling, Jason J.; Garcia, Pablo A.

2013-01-01

The authors tested a model based on the satisfaction model of social cognitive career theory (SCCT) that links college students' affective commitment to their major (the emotional identification that students feel toward their area of study) with career decision self-efficacy (CDSE) and career outcome expectations. Results indicate that CDSE…

Early Adolescent Depressive Symptoms: Prediction from Clique Isolation, Loneliness, and Perceived Social Acceptance

ERIC Educational Resources Information Center

Witvliet, Miranda; Brendgen, Mara; van Lier, Pol A. C.; Koot, Hans M.; Vitaro, Frank

2010-01-01

This study examined whether clique isolation predicted an increase in depressive symptoms and whether this association was mediated by loneliness and perceived social acceptance in 310 children followed from age 11-14 years. Clique isolation was identified through social network analysis, whereas depressive symptoms, loneliness, and perceived…

Right Temporoparietal Gray Matter Predicts Accuracy of Social Perception in the Autism Spectrum

ERIC Educational Resources Information Center

David, Nicole; Schultz, Johannes; Milne, Elizabeth; Schunke, Odette; Schöttle, Daniel; Münchau, Alexander; Siegel, Markus; Vogeley, Kai; Engel, Andreas K.

2014-01-01

Individuals with an autism spectrum disorder (ASD) show hallmark deficits in social perception. These difficulties might also reflect fundamental deficits in integrating visual signals. We contrasted predictions of a social perception and a spatial-temporal integration deficit account. Participants with ASD and matched controls performed two…