A comparison of email networks and off-line social networks: A study of a medium-sized bank

Recently there has been a surge in the availability of online data concerning the connections between people, and these online data are now widely used to map the social structure of communities. There has been little research, however, on how these new types of relational data correspond to classical measures of social networks. To fill this gap, we contrast the structure of an email network with the underlying friendship, communication, and advice seeking networks. Our study is an explorative case study of a bank, and our data contains emails among employees and a survey of the ego networks of the employees. Through calculating correlations with QAP standard errors and estimating exponential random graph (ERG) models, we find that although the email network is related to the survey-based social networks, email networks are also significantly different: while off-line social networks are strongly shaped by gender, tenure, and hierarchical boundaries, the role of these boundaries are much weaker in the email network.     

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.     

Dynamic social media affiliations among UK politicians

Inter-personal affiliations and coalitions are an important part of politicians’ behaviour, but are often difficult to observe. Since an increasing amount of political communication now occurs online, data from online interactions may offer a new toolkit to study ties between politicians; however, the methods by which robust insights can be derived from online data require further development, especially around the dynamics of political social networks. We develop a novel method for tracking the evolution of community structures, referred to as ‘multiplex community affiliation clustering’ (MCAC), and use it to study the online social networks of Members of Parliament (MPs) and Members of the European Parliament (MEPs) in the United Kingdom. Social interaction networks are derived from social media (Twitter) communication over an eventful 17-month period spanning the UK General Election in 2015 and the UK Referendum on membership of the European Union in 2016. We find that the social network structure linking MPs and MEPs evolves over time, with distinct communities forming and re-forming, driven by party affiliations and political events. Without including any information about time in our model, we nevertheless find that the evolving social network structure shows multiple persistent and recurring states of affiliation between politicians, which align with content states derived from topic analysis of tweet text. These findings show that the dominant state of partisan segregation can be challenged by major political events, ideology, and intra-party tension that transcend party affiliations.     

The Swiss StudentLife Study: Investigating the emergence of an undergraduate community through dynamic,multidimensional social network data

The Swiss StudentLife Study (SSL Study) is a longitudinal social network data collection conducted in three undergraduate student cohorts (N₁ = 226, N₂ = 261, N₃ = 660) in 2016−2019. The main goal of the study was to understand the emergence of informal student communities and their effects on different individual outcomes, such as well-being, motivation, and academic success. To this end, multiple dimensions of social ties were assessed, combining computer-based surveys, social sensors, social media data, and field experiments. The dynamics of these social networks were measured on various time scales. In this paper, we present the design and data collection strategy of the SSL Study. We discuss practical challenges and solutions related to the data collection in four areas that were key to the success of our project: study design, research ethics, communication, and population definition.     

The potential of online social networking data for augmenting the study of high-risk personal networks among young men who have sex with men at-risk for HIV

Capturing dynamics in high-risk personal networks is essential for preventing HIV transmission. Online social networking data offer incentive to augment traditional selfreported approaches for network enumeration. To explore what online networks reveal about dynamics among high-risk associates, we examine the relationship between egocentric confidant and sex networks and personal Facebook friendship networks of a cohort of young Black men who have sex with men. Although overlap exists between self-reported and Facebook associates, the stabilities of each were unrelated. Confidants who were also Facebook friends with a respondent were, however, more likely to be retained. Thus, Facebook networks contain stable confidants.     

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.     

Who benefits from network intervention programs? TERGM analysis across ten Philippine low-income communities

Building social capital and strengthening social networks among members of low-income communities has been recommended as a potential pathway out of poverty. However, it is not clear how network-strengthening interventions and community-based programs interact with pre-existing networks and power structures. We examine the impact of one such intervention in ten low income communities in the Philippines. The intervention is a standardized program of a faith-based organization implemented in thousands of communities in multiple countries. It brings together low-income individuals in each community for 16 weekly sessions about health, income generation, and Christian values. An important but yet unmeasured goal of the intervention is the strengthening of social networks among the participants. We measured the social networks before and after the intervention and analysed their changes both separately and jointly for all ten communities with temporal exponential random graph models (TERGM). We modelled the post-intervention network structures conditioning on the pre-intervention networks, pre-intervention node attributes, and attribute changes through the intervention. We found social engagement (measured by social visits to others) to moderate most consistently the effects of the intervention across the ten communities. Those who were more socially engaged consistently strengthened their networks through the intervention. By contrast, some network mechanisms strongly diverged between the communities. In particular, religiosity was positively associated with gaining social links through this faith-based intervention in some communities and negatively in others. Similar communities may in some aspects react to the same intervention in opposite ways—a phenomenon that should be further explored through studies of larger numbers of comparable networks.     

Change in Covert Social Movement Networks: The ‘Inner Circle’ of the Provisional Irish Republican Army

In this paper, we contribute to both the growing body of literature on social movement networks and the growing body of literature on change in networks by exploring patterns and mechanisms of change within the network of the ‘inner circle’ of the Provisional Irish Republican Army. Specifically, we focus upon the period between 1969 (when it formed) and 1988 (the last point for which we have been able to gather good data). Our primary aims are substantive. We want to know how this network changed over time. In addition, however, our analysis identifies changes which other analysts might look for in their networks and offers methodological suggestions for those who, like us, find that their networks do not meet the assumptions of mainstream approaches to modelling network dynamics. There is a further dimension to the paper, however. We are studying a covert social movement network. This is a special type of movement network whose organisation and dynamics are predicted to vary from other movement networks. Some have suggested that they are inclined to be relatively static because the need for trust within them is so great and the risk to whatever they hold secret so considerable when new ties are formed that their members tend only to recruit within the pool of their pre-existing ties and actively seek to minimise recruitment and the formation of new ties. One of the aims of our paper was to determine whether and to what extent this is so.     

Social Movements and Social Networks: Introduction

In this Introduction we provide a brief literature review of work on social networks and social movements, a brief introduction to certain key concepts and debates in social network analysis, and a brief introduction to the articles which follow in the special issue.     

The structure of online social networks mirrors those in the offline world

We use data on frequencies of bi-directional posts to define edges (or relationships) in two Facebook datasets and a Twitter dataset and use these to create ego-centric social networks. We explore the internal structure of these networks to determine whether they have the same kind of layered structure as has been found in offline face-to-face networks (which have a distinctively scaled structure with successively inclusive layers at 5, 15, 50 and 150 alters). The two Facebook datasets are best described by a four-layer structure and the Twitter dataset by a five-layer structure. The absolute sizes of these layers and the mean frequencies of contact with alters within each layer match very closely the observed values from offline networks. In addition, all three datasets reveal the existence of an innermost network layer at ∼1.5 alters. Our analyses thus confirm the existence of the layered structure of ego-centric social networks with a very much larger sample (in total, >185,000 egos) than those previously used to describe them, as well as identifying the existence of an additional network layer whose existence was only hypothesised in offline social networks. In addition, our analyses indicate that online communities have very similar structural characteristics to offline face-to-face networks.     

Latino Faces,Corporate Ties: Latino Advocacy Organizations and Their Board Membership

Although they have increased exponentially since the 1960s, social scientists know little about ethnic advocacy organizations. These nonprofits are important bridges between underresourced communities and mainstream funding organizations and their directors are established ethnic leaders. Sociologists study interlocking directorates—or shared board membership—to understand how organizations fit together within broader social networks. Network concepts, particularly the theory of institutional isomorphism, suggest that organizations are likely to be similar to the extent they are connected and operate within a common organizational field. We apply this logic to Latino advocacy organizations to examine the underlying source of cohesion across this ethnic field. We ask whether the organizations are tied by interlocking directorates of ethnic elites who sit on their boards of directors or if board members' common affiliation with other elite institutions creates the structural conditions that facilitate potential ideological or behavioral similarity. A social network analysis of five prominent Latino advocacy organizations reveals support for both hypotheses: Latino board members are both embedded in ethnic‐based networks and entrenched within elite organizational webs. This suggests that ethnic elites who sit on the boards of Latino advocacy organizations are also corporate elites, selected for the social capital they bring to these nonprofits.     

The role of networks of practice and webs of influencers on farmers' engagement with and learning about agricultural innovations

Drawing on the UK research project, ‘Farmers’ understandings of GM crops within local communities’, this paper considers the application of the concepts of communities of practice and networks of practice in the agricultural context. A brief review of theories about communities of practice and networks of practice is given and some of our findings are discussed in the context of those theories.Farmers were found to be a particular type of network of practice, characterised by a weak organisational framework but with a relatively stable network of other communities of practice (or networks of practice) they interact with, which we have called a ‘web of influencers on practice’. Together, farmers’ network of practice and their web of influencers on practice represent the whole environment in which learning may occur, and so provide insights into their social learning system. Most farmers have to work at the boundary of their network of practice and their web of influencers, which creates a significant load on their knowledge management. This is in contrast to other networks of practice where only some members take on this boundary brokering role. The paper concludes that these theories (on networks and communities of practice) provide a useful lens through which to view farmers and their practice, highlighting important points for policy. However, in such contexts these theories need to be extended to include the role of a broader ‘web of influencers on practice’.     

Community and Social Capital: What Is the Difference?

The ideas of community and social capital have received much attention in the last decade, but are plagued by a multitude of conceptualizations, definitions, and operationalizations. This confusion is problematic for both researchers and policymakers trying to use these concepts. While numerous efforts have been made to clarify "social capital" and "community," too often the two are simply conflated. This paper attempts to distinguish between them by looking at the various ways they are related in concrete examples. Drawn largely from the literature, five examples are offered that together describe the complex interactions of place-based communities and social capital networks. These examples also demonstrate distinctions between community and social capital with regard to boundaries, the qualities of social relations and trust in each, instrumentality, the consequences of one for the other, and issues related to multiple communities in a single place. It is hoped that these distinctions will inform the ongoing efforts to develop unique and useful conceptualizations of these two terms.     

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.     

The subjective dimension of social isolation: A qualitative investigation of older adults' experiences in small social support networks

In the aging literature, social isolation has been primarily defined in terms of reduced support network size and low frequency of social contacts. Having a small social support network is associated with social isolation and an increased risk of physical and emotional vulnerability. However, this conceptualization ignores the contributions of a host of other factors, including life experiences, family dynamics, and long-term patterns of socialization. This paper argues that alongside quantitative assessments of support systems, the application of a life course perspective is needed to understand small social networks as lived experience. We report on findings from 28 in-depth interviews with older adults identified as being at risk of social isolation on the basis of the self-reported size of their social networks. We discuss these participants' experiences in the context of significant life course transitions such as marriage and widowhood.     

Collective action and network change

Network models of collective action commonly assume fixed social networks in which ties influence participation through social rewards. This implies that only certain ties are beneficial from the view of individual actors. Accordingly, in this study we allow that actors strategically revise their relations. Moreover, in our model actors also take into account possible network consequences in their participation choices. To handle the interrelatedness of networks and participation, we introduce new equilibrium concepts. Our equilibrium analysis suggests that structures that tend to segregate contributors from free riders are stable, but costless network change only promotes all-or-nothing participation and complete networks.     

Partitioning signed social networks

Structural balance theory has proven useful for delineating the blockmodel structure of signed social networks. Even so, most of the observed signed networks are not perfectly balanced. One possibility for this is that in examining the dynamics underlying the generation of signed social networks, insufficient attention has been given to other processes and features of signed networks. These include: actors who have positive ties to pairs of actors linked by a negative relation or who belong to two mutually hostile subgroups; some actors that are viewed positively across the network despite the presence of negative ties and subsets of actors with negative ties towards each other. We suggest that instead viewing these situations as violations of structural balance, they can be seen as belonging to other relevant processes we call mediation, differential popularity and internal subgroup hostility. Formalizing these ideas leads to the relaxed structural balance blockmodel as a proper generalization of structural balance blockmodels. Some formal properties concerning the relation between these two models are presented along with the properties of the fitting method proposed for the new blockmodel type. The new method is applied to four empirical data sets where improved fits with more nuanced interpretations are obtained.     

Social context and network formation: An experimental study

Recently, there has been increasing interest in determining which social network structures emerge as a consequence of the conscious actions of actors. Motivated by the belief that “networks matter” in reaching personal objectives, it is a natural assumption that actors try to optimize their network position. Starting from the notion that an optimal network position depends on the social context, we examine how actors change their networks to reach better positions in various contexts. Distinguishing between three social contexts (a neutral context, a context in which closed triads are costly, and a context in which closed triads are beneficial), theoretical results predict that emerging networks are contingent on the incentives that are present in these contexts. Experiments are used to test whether networks that are theoretically predicted to be stable are also stable experimentally. We find that emerging networks correspond to a large extent with the predicted networks. Consequently, they are contingent on the incentives present in various social contexts. In addition, we find that subjects tend to form specific stable networks with a higher probability than predicted, namely, efficient networks and networks in which everyone is equally well off.     

Contemporary urban culture: how community structures endure in an individualised society

This paper examines the ways in which socio-cultural norms have shifted to accommodate higher levels of autonomy in urban communities. Largely critiquing traditional concepts of community as well as current dystopian perspectives on the fluid and vapid state of social organisation, it will show how individualism has been incorporated into societal norms, producing highly autonomous personalised networks that, when combined with large amounts of social interaction and imaginative cultural appropriation, create the common social and cultural practices emblematic of community structure. It also illustrates how many activities, traditionally viewed as indicative of social decay, are socially productive, in that they go towards generating the common bonds and world-views that unite individuals across urban landscapes. Focusing particularly on the spaces of community interaction, the construction of common identities and common sense of belonging, this paper sets out to explore alternative modes of community creation and enactment in a contemporary urban environment.