Social Contagion and General Diffusion Models of Adolescent Religious Transitions: A Tutorial,and EMOSA Applications

Epidemic Models of the Onset of Social Activities (EMOSA) describe behaviors that spread through social networks. Two social influence methods are represented, social contagion (one-to-one spread) and general diffusion (spread through cultural channels). Past models explain problem behaviors—smoking, drinking, sexuality, and delinquency. We provide review, and a tutorial (including examples). Following, we present new EMOSA models explaining changes in adolescent and young adult religious participation. We fit the model to 10 years of data from the 1997 U.S. National Longitudinal Survey of Youth. Innovations include a three-stage bi-directional model, Bayesian Markov Chain Monte Carlo (MCMC) estimation, graphical innovations, and empirical validation. General diffusion dominated rapid reduction in church attendance during adolescence; both diffusion and social contagion explained church attendance stability in early adulthood.     

Exponential random graph models for little networks

Statistical models for social networks have enabled researchers to study complex social phenomena that give rise to observed patterns of relationships among social actors and to gain a rich understanding of the interdependent nature of social ties and actors. Much of this research has focused on social networks within medium to large social groups. To date, these advances in statistical models for social networks, and in particular, of Exponential-Family Random Graph Models (ERGMS), have rarely been applied to the study of small networks, despite small network data in teams, families, and personal networks being common in many fields. In this paper, we revisit the estimation of ERGMs for small networks and propose using exhaustive enumeration when possible. We developed an R package that implements the estimation of pooled ERGMs for small networks using Maximum Likelihood Estimation (MLE), called “ergmito”. Based on the results of an extensive simulation study to assess the properties of the MLE estimator, we conclude that there are several benefits of direct MLE estimation compared to approximate methods and that this creates opportunities for valuable methodological innovations that can be applied to modeling social networks with ERGMs.     

Situated (un-)learning in software design: a deconstructive approach

Constructive technology assessment aims at anticipating societal impacts of technological innovations and suggests incorporating reflexivity and social learning into technology development. Social learning involves fostering the ability of diverse social actors to cultivate sociotechnical critical skills, thus allowing technological and social change to be governed with consideration for social values and diverging interests. Based on this demand, our paper presents a discourse-theoretical, interventionist approach to software design introducing deconstruction and (un-)learning as reflective practices to guide development processes. Inspired by Donna Haraway’s focus on power relations in technoscience culture, our approach—called ‘deconstructive design’—traces how structures such as in/formal hierarchies and discursive hegemonies affect the development processes and design decisions of teams or communities of practices. The underlying deconstructivist methodology refers to practice-based concepts of situated learning. Thus, it locates a potential for value-based intervention at the micro/meso-level of everyday work practices.     

Equicentrality and network centralization: A micro–macro linkage

This paper investigates a linkage between micro- and macrostructures as an intrinsic property of social networks. In particular, it examines the linkage between equicentrality [Kang, S.M., 2007. A note on measures of similarity based on centrality. Social Networks 29, 137–142] as a conceptualization of a microstructural process (i.e., the likelihood of social actors to be connected with similarly central others) and network centralization as a macrostructural construct, and shows that they have a negative linear association. In other words, when actors are connected with similarly central alters (i.e., high equicentrality), the overall network centralization is low. Conversely, when highly central actors are connected with low-centrality actors (i.e., low equicentrality), the overall network centralization is high. The relationship between degree equicentrality and degree centralization is more significant in observed networks, especially those evolving over time, as compared to random networks. An application of this property is given by venture capital co-investment networks.     

Evolutionary Process of Social Capital Formation through Community Currency Organizations: The Japanese Case

Community currency systems are said to influence the revival of communities by promoting either local economic growth or social capital accumulation. However, no empirical studies have examined the multiple competing mechanisms for providing social support through transactional networks among participants. The current study connects network structural concepts to theories of social capital, transaction costs, homophily, and resource dependency at multiple levels and evaluates transactional relationships for community rebuilding and local economic development. We examine the evolutionary process of dynamic networks among local residents or organization members with network configurations in one of the largest Japanese community currency systems, “Peanuts.” Using longitudinal network data over 12 years for approximately 1400 actors, we conclude that the evolution and achievement of transactional network dynamics and partner selections differ between the two groups of participants: individual members and organization members. We also provide practical implications for sustaining participants’ transactions and commitment.     

Social Networks and Social Settings: Developing a Coevolutionary View

One way to think about social context is as a sample of alters. To understand individual action, therefore, it matters greatly where these alters may be coming from, and how they are connected. According to one vision, connections among alters induce local dependencies—emergent rules of social interaction that generate endogenously the observed network structure of social settings. Social selection is the decision of interest in this perspective. According to a second vision, social settings are collections of social foci—physical or symbolic locales where actors meet. Because alters are more likely to be drawn from focused sets, shared social foci are frequently considered as the main generators of network ties, and hence of setting structure. Affiliation to social foci is the decision of central interest in this second view. In this paper we show how stochastic actor–oriented models (SAOMs) originally derived for studying the dynamics of multiple networks may be adopted to represent and examine these interconnected systems of decisions (selection and affiliation) within a unified analytical framework. We illustrate the empirical value of the model in the context of a longitudinal sample of adolescent participating in the Glasgow Teenage Friends and Lifestyle Study. Social selection decisions are examined in the context of networks of friendship relations. The analysis treats musical genres as the main social foci of interest.     

Assessing organizational capacity for diffusion: A school-based social network analysis case study

The purposeful design of social networks is increasingly recognized as a fundamental organizational improvement strategy. In the PK-12 education sector, school-based teacher collaboration is the primary vehicle through which educators are able to gain access to essential social capital, and through which leaders promulgate diffusion of innovation and continuous organizational learning. In partnership with school administrators, the authors undertook an evaluation to examine the size, structure, and composition of school-based networks. Social network analysis (SNA) was used to measure and visualize connections (or lack thereof) of ties between teams and between educators. Isolate and disconnected network actors were revealed through visual inspection of the sociograms. Administrators used findings to reconfigure team membership to enhance teacher ability to give and receive support and collaboratively problem-solve, and to ensure greater capacity for diffusion of instructional innovation and organizational learning. This paper contributes to the field’s understanding of how evaluators and organizational leaders can use SNA to measure, visualize, and more purposefully design effective patterns of connection between people through which professional knowledge, support, and innovation will travel.     

A New Model for Information Diffusion in Heterogeneous Social Networks

This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information during the information diffusion process. The model provides predictions of diffusion times in a given network at the global, dyadic, and individual levels. This leads to straightforward generalizations of network measures, such as closeness centrality and betweenness centrality, for research problems that focus on the efficiency of information transfer in a network. We analyze in detail how information diffusion times and centrality measures depend on a series of network measures, such as degrees and bridges. One important finding is that predictions about the time actors need to spread information in the network differ considerably between the new and old models, while the predictions about the time needed to receive information hardly differ. Finally, some cautionary remarks are made about using the model in empirical research.     

NETWORK IMPACT OF SOCIAL INNOVATION INITIATIVES IN MARGINALISED RURAL COMMUNITIES

The marginalised rural communities are characterised by societal challenges, such as isolation, lack of job opportunities, land abandonment, low quality of life and generally low education. Social Innovation (SI) initiatives may represent an opportunity to strengthen relationships among the members of rural community, by means of the alteration of the existing social networks. In this way, more exchange of information is expected, paving the way for the creation of professional collaborations among firms and other actors. This paper aims at proposing a short-term evaluation framework of effectiveness of a SI initiative in terms of reconfiguration of the social network structure. The described empirical case study is VàZapp’, a rural hub located in Southern Italy, which provides innovative solutions to activate social relations amongst farmers, altering hence their network. A well-referenced SI theoretical model, developed within the H2020 project SIMRA (Social Innovation in Marginalised Rural Areas), and the methodology of Social Network Analysis (SNA) were used to verify and measure quantitative and qualitative indicators affected by network intervention activated by VàZapp’ initiative. Results show that this SI initiative worked effectively, leading to a +308% in the number of relations and +250% in social network density. In addition, an evident improvement in the quality of the social relations was found, especially in cases where there are direct engagements within VàZapp’. Outcomes suggest that supporting and promoting SI initiatives could become a central discussion point for the rethinking of rural development policies focused on regeneration of social relations’ structure.     

More social movements or fewer? Beyond political opportunity structures to relational fields

If social movements are an attempt by “outsiders” to gain leverage within politics, then one might expect the global spread of democracy to reduce social movement activity. This article argues the reverse. Granted, many past social movements, such as women's rights and civil rights, were efforts to empower the disenfranchised. However, this is not typical. Rather, social movements and protest tactics are more often part of a portfolio of efforts by politically active leaders and groups to influence politics. Indeed, as representative governance spreads, with the conviction by all parties that governments should respond to popular choice, then social movements and protest will also spread, as a normal element of democratic politics. Social movements should therefore not be seen as simply a matter of repressed forces fighting states; instead they need to be situated in a dynamic relational field in which the ongoing actions and interests of state actors, allied and counter-movement groups, and the public at large all influence social movement emergence, activity, and outcomes.     

Community Connections: Social Capital and Community Success1

This article examines the impact of two types of community social capital—ties between civic organizations formed through shared members and ties between residents formed through socializing in local gathering places—on residents’ subjective appraisals of community success. Community social capital studies tend to focus on the first of these types of ties, networks of civic engagement, while the second, gathering place networks, has received relatively little scholarly attention. Studying both allows me to assess the formal and informal arenas of community sociability, providing a more thorough understanding of social capital and community life. I assess the effects of community‐level social capital networks on the individual‐level experience of residing in the community using survey data on 9,962 residents from 99 small towns in Iowa. This rich data set allows me to avoid two shortcomings common in social capital research: I construct genuine network measures of social capital (rather than infer network structure from community attributes) and conduct multi‐level analyses (rather than rely on disaggregation). My findings indicate both types of social capital are positively and significantly associated with resident ratings of community success, suggesting community networks—in both the formal and informal sectors—have important consequences for small towns and their residents.     

Centrality in affiliation networks

This paper discusses the conceptualization, measurement, and interpretation of centrality in affiliation networks. Although centrality is a well-studied topic in social network analysis, and is one of the most widely used properties for studying affiliation networks, virtually all discussions of centrality and centralization have concerned themselves with one-mode networks. Bonacich's work on simultaneous group and individual centralities is a notable exception (Social Networks, 1991, 13, 155–168). I begin by outlining the distinctive features of affiliation networks and describe four motivations for centrality indices in affiliation networks. I then consider properties of some existing centrality indices for affiliation networks, including the relationship between centralities for actors and events in these networks, and present a new conceptualization of centrality that builds on the formal properties of affiliation networks and captures important theoretical insights about the positions of actors and events in these networks. These centralities are then illustrated on Galaskiewicz's data on club and board memberships of a sample of corporate executive officers (Social Organization of an Urban Grants Economy. New York: Academic Press, 1985). The conclusion to this paper discusses strengths and weaknesses of centrality indices when applied to affiliation networks.     

Introduction: global knowledge and advocacy networks

As global and regional networks proliferate, one important aspect of their operations has been the exchange of knowledge, information and expertise. ‘Global knowledge networks’ have become important components of the global political economy. Within these networks key knowledge institutions and actors can be development agencies, foundations, think‐tanks, universities, consultancy firms as well as individual experts and academics. A primary mechanism for the spread of their knowledge has been through global and regional networks. The article evaluates first, concepts of networks, especially the epistemic community and transnational issue network frameworks; second, theories about international diffusion of ideas; and third, some of the literature on the links between ideas and politics. Control over knowledge and information is important to policy making. Additionally, the status and prestige associated with scholarly expertise and professional training is politically empowering for individual experts consulted or co‐opted into policy making. Yet, norms and values cannot be divorced from ‘scientific advice’ especially when knowledge gains greater impact through advocacy and alliance with societal forces.     

Minutes,Meeting of Council: The Ohio Valley Sociological Society,Statler Hilton Hotel,Detroit, Michigan,Thursday, May 2, 1968

Abstract

A perennial issue in both rural and urban sociology has been whether or not size of place is associated with differences in the way that individuals relate to one another. This paper examines the relationship between size of place and the structural properties of personal social networks through the mediating effects of residential stability. Social network data from the General Social Survey (National Opinion Research Center 1990) provide support for the hypothesis that residential stability explains the association between size of place and social network density. The implications of these findings for community theory are discussed.     

Characteristics And Types Of Participation In Social Worlds

The concept of social world is given greater analytical power by categorizing differential participation through a typology of social types—strangers, tourists, regulars, and insiders. These trans-situational social types are examined in terms of their commitment, relationships, experiences, and orientation to social worlds. Social worlds are also discussed in terms of three qualities of interaction—relevance, accessibility, and receptivity.     

Investing in people: The role of social networks in the diffusion of a large-scale fraud

This paper draws from social network analysis and diffusion theory to study the case of a mortgage fraud that spread undetected for five years in British Columbia, Canada. The fraud is studied from the point of view of 559 victims who unknowingly invested in the Ponzi scheme which defrauded 2285 investors for a total of $ 240 million dollars. Results show diffusion played a role in the success of the Eron fraud even though the fraud ended before it reached the final stages of a classic diffusion process. A closer look at the social structure of the Eron network revealed the elements that made the fraud successful: (1) change agents, particularly Eron principals and Eron employees invested their personal time and effort recruiting investors; (2) independent brokers actively spread the fraud to their clients; and (3) opinion leaders, investors themselves, unknowingly spread the fraud through their social networks by recruiting their friends and family to invest in Eron.     

Cluster analysis of multiplex networks: Defining composite network measures

Social relations are multiplex by nature: actors in a group are tied together by various types of relationships. To understand and explain group processes it is, therefore, important to study multiple social networks simultaneously in a given group. However, with multiplexity the complexity of data also increases. Although some multivariate network methods (e.g. Exponential Random Graph Models, Stochastic Actor-oriented Models) allow to jointly analyze multiple networks, modeling becomes complicated when it focuses on more than a few (2–4) network dimensions. In such cases, dimension reduction methods are called for to obtain a manageable set of variables. Drawing on existing statistical methods and measures, we propose a procedure to reduce the dimensions of multiplex network data measured in multiple groups. We achieve this by clustering the networks using their pairwise similarities, and constructing composite network measures as combinations of the networks in each resulting cluster. The procedure is demonstrated on a dataset of 21 interpersonal network dimensions in 18 Hungarian high-school classrooms. The results indicate that the network items organize into three well-interpretable clusters: positive, negative, and social role attributions. We show that the composite networks defined on these three relationship groups overlap but do not fully coincide with the network measures most often used in adolescent research, such as friendship and dislike.     

Organizations,coalitions, and movements

This article uses empirical evidence on networks of voluntary organizations mobilizing on ethnic minority, environmental, and social exclusion issues in two British cities, to differentiate between social movement processes and other, cognate collective action dynamics. Social movement processes are identified as the building and reproducing of dense informal networks between a multiplicity of actors, sharing a collective identity, and engaged in social and/or political conflict. They are contrasted to coalitional processes, where alliances to achieve specific goals are not backed by significant identity links, and organizational processes, where collective action takes place mostly in reference to specific organizations rather than broader, looser networks.     

Analysing networks of networks

We consider data with multiple observations or reports on a network in the case when these networks themselves are connected through some form of network ties. We could take the example of a cognitive social structure where there is another type of tie connecting the actors that provide the reports; or the study of interpersonal spillover effects from one cultural domain to another facilitated by the social ties. Another example is when the individual semantic structures are represented as semantic networks of a group of actors and connected through these actors’ social ties to constitute knowledge of a social group. How to jointly represent the two types of networks is not trivial as the layers and not the nodes of the layers of the reported networks are coupled through a network on the reports. We propose to transform the different multiple networks using line graphs, where actors are affiliated with ties represented as nodes, and represent the totality of the different types of ties as a multilevel network. This affords studying the associations between the social network and the reports as well as the alignment of the reports to a criterion graph. We illustrate how the procedure can be applied to studying the social construction of knowledge in local flood management groups. Here we use multilevel exponential random graph models but the representation also lends itself to stochastic actor-oriented models, multilevel blockmodels, and any model capable of handling multilevel networks.     

The contribution of the intervention in social networks and community social work at the local level to social and human development

ABSTRACT

The primary task of community social work is building social networks by reinforcing people's resources and those of the different environmental and social contexts from three dimensions: personal development, social development and organisational development. The new information technologies today establish a relationship of communication with local communities and citizens that promotes proximity to social networks. Social intervention is supported by a set of methods from human geography that can be used as tools to create maps of the territory and the networks for planning, diagnosing and classifying the management of community network intervention. In this discussion we set out to analyse the contribution of the intervention in social networks as a means of achieving a new configuration of social networks at the local level. This information is obtained from semi-structured interviews with social workers and other professionals in the social sphere in municipalities with over 100,000 inhabitants in the Madrid region (Spain). The research results show that intervention in social networks locally multiplies the opportunities to enhance the quality of people's social relationships, thus expanding their social support by strengthening their bonds, their personal network and support systems; secondly, it increases empowerment to facilitate a type of intervention to strengthen human potential and to gain autonomy and full citizenship.