Social context,spatial structure and social network structure

Frequently, social networks are studied in their own right with analyses devoid of contextual details. Yet contextual features – both social and spatial – can have impacts on the networks formed within them. This idea is explored with five empirical networks representing different contexts and the use of distinct modeling strategies. These strategies include network visualizations, QAP regression, exponential random graph models, blockmodeling and a combination of blockmodels with exponential random graph models within a single framework. We start with two empirical examples of networks inside organizations. The familiar Bank Wiring Room data show that the social organization (social context) and spatial arrangement of the room help account for the social relations formed there. The second example comes from a police academy where two designed arrangements, one social and one spatial, powerfully determine the relational social structures formed by recruits. The next example is an inter-organizational network that emerged as part of a response to a natural disaster where features of the improvised context helped account for the relations that formed between organizations participating in the search and rescue mission. We then consider an anthropological example of signed relations among sub-tribes in the New Guinea highlands where the physical geography is fixed. This is followed by a trading network off the Dalmatian coast where geography and physical conditions matter. Through these examples, we show that context matters by shaping the structure of networks that form and that a variety of network analytic tools can be mobilized to reveal how networks are shaped, in part, by social and spatial contexts. Implications for studying social networks are suggested.     

Spatial distance and mobile business social network density

Following the increasing adoption of mobile communication, scholars have shown interest in the role of place on the structure of mobile social networks. The purpose of this study is to investigate the association between spatial distance and the closure and diversity of businesses mobile social networks. We used a database that aggregates actual mobile communication patterns of business users of a large Israeli cell phone company (n?= 16,199). Our findings, among a large sample of businesses, provide support for the place and mobile communication perspective. The results reveal a negative association between spatial distance and mobile business communication networks. As spatial distance between business network members increases, business social ties through mobile communication decreases. Furthermore, the results also revealed a negative association between spatial distance and mobile network density. As the spatial distance between business users increases, the density of the mobile communication network diminishes. Physical proximity promotes the development of dense business networks. The implications of the findings are discussed.     

Residential mobility and the spatial dispersion of personal networks: Effects on social support

Using a representative national sample of personal networks, this article explores how the spatial dispersion of networks, residential mobility and social support are linked. Three issues will be addressed here. Firstly, how is the spatial dispersion of personal networks related to individuals’ social characteristics, network composition and residential mobility? Secondly, how do the spatial dispersion of networks, residential mobility and their combined effect influence the number and (thirdly) the structure of emotional support ties? Results showed that the extent of the support was affected neither by the geographical distribution of the networks nor by residential mobility. Living far from one's birthplace, however, exerted two distinct, and opposite effects on the support network structure. On the one hand, mobility led to high spatial dispersion of personal contacts, which in turn favored a sparsely knit network centered around the mobile individual. On the other hand, by controlling for the effect of distance between the contacts, we found that individuals that cited long-distance ties tended to be part of more transitive support networks than those that cited local ties. We interpreted the latter effect as evidence that transitive ties may survive greater spatial distances than intransitive ones. These findings are discussed in view of spatial mobility and social network research.     

Measurement and theory in legislative networks: The evolving topology of Congressional collaboration

The examination of legislatures as social networks represents a growing area of legislative scholarship. We examine existing treatments of cosponsorship data as constituting legislative networks, with measures aggregated over entire legislative sessions. We point out ways in which the direct application of models from the social networks literature legislative networks aggregated over entire sessions could potentially obscure interesting variation at different levels of measurement. We then present an illustration of an alternative approach, in which we analyze disaggregated, dynamic networks and utilize multiple measures to guard against overly measure-dependent inferences. Our results indicate that the cosponsorship network is a highly responsive network subject to external institutional pressures that more aggregated analyses would overlook.     

Geographical variability and network structure

In this paper, we explore the potential implications of geographical variability for the structure of social networks. Beginning with some basic simplifying assumptions, we derive a number of ways in which local network structure should be expected to vary across a region whose population is unevenly distributed. To examine the manner in which these effects would be expected to manifest given realistic population distributions, we then perform an exploratory simulation study that examines the features of large-scale interpersonal networks generated using block-level data from the 2000 U.S. Census. Using a stratified sample of micropolitan and metropolitan areas with populations ranging from approximately 1000 to 1,000,000 persons, we extrapolatively simulate network structure using spatial network models calibrated to two fairly proximate social relations. From this sample of simulated networks, we examine the effect of both within-location and between-location heterogeneity on a variety of structural properties. As we demonstrate, geographical variability produces large and distinctive features in the “social fabric” that overlies it; at the same time, however, many aggregate network properties can be fairly well-predicted from relatively simple spatial demographic variables. The impact of geographical variability is thus predicted to depend substantially on the type of network property being assessed, and on the spatial scale involved.     

Networks and geography: Modelling community network structures as the outcome of both spatial and network processes

This paper focuses on how to extend the exponential random graph models to take into account the geographical embeddedness of individuals in modelling social networks. We develop a hierarchical set of nested models for spatially embedded social networks, in which, following Butts (2002), an interaction function between tie probability and Euclidean distance between nodes is introduced. The models are illustrated by an empirical example from a study of the role of social networks in understanding spatial clustering in unemployment in Australia. The analysis suggests that a spatial effect cannot solely explain the emergence of organised network structure and it is necessary to include both spatial and endogenous network effects in the model.     

The role of network setting and gender in online content popularity

In this study, we explore the role of specific network structures that enhance social capital and assess the extent to which gender, social ties, and communication interaction relate to content popularity within online social networks (OSNs). Our results are based on an extensive OSN data set, containing over 100,000 members, connected by over 1.7 million links. The findings indicate that content popularity inference is more accurate when considering activity interaction among users and that network structures known as advantageous for amassing social capital in the offline environment are relevant online as well. We conclude by discussing how gender mediates the correlation between some network measures and the growth of users’ content popularity and provide a potential explanation for the emergence of gender differences.     

Place,space, networks,and the sustainability of collective action: the Madres de Plaza de Mayo

This article provides a framework for analysing social movements and explaining how collective action can be sustained through networks. Drawing on current relational views of place and space, I offer a spatialized conception of social networks that critically synthesizes network theory, research on social movements, and the literature on the spatial dimensions of collective action. I examine the historic and contemporary network geographies of a group of human rights activists in Argentina (the Madres de Plaza de Mayo) and explain the duration of their activism over a period of more than two decades with regard to the concept of geographic flexibility. To be specific, first I show how, through the practice of place‐based collective rituals, activists have maintained network cohesion and social proximity despite physical distance. Second, I examine how the construction of strategic networks that have operated at a variety of spatial scales has allowed the Madres to access resources that are important for sustaining mobilization strategies. Finally, I discuss how the symbolic depiction of places has been used as a tool to build and sustain network connections among different groups. I conclude by arguing that these three dimensions of the Madres’ activism account for their successful development of geographically flexible networks, and that the concept of geographic flexibility provides a useful template for studies of the duration and continuity of collective action.     

The impact of social networks on the occupational status of migrants

This paper postulates that there is a continuous exchange of information and knowledge between those who share the common bond of having migrated to the US. The individual components of this information exchange constitute social networks. The 2 hypotheses tested are 1) immediate social networks and people known in the US facilitate the flow of information both to new migrants and between established migrants, thus promoting upward social mobility; and 2) access to broader network ties, organization membership, extra-ethnic friendships, and familiarity with established institutions smooths the transition process, resulting in increased social position. The data used comes from a study conducted in 1982-1983 in 4 Mexican sending communities (2 rural, 2 urban), for a total of 440 migrants. Results show that migrants in every socioeconomic bracket reported access to some or all social network characteristics. There was contact with either a family member or acquaintances from the migrants' town of origin. Over 50% of migrants reported knowing many fellow townspeople. Twice as many migrants belong to a sports club as to a social or religious organization. Very few rural migrants report knowing no townspeople, while 32% of urban migrants claim no knowledge of fellow migrants from their town of origin. Urban origin migrants report more contacts with those of other ethnicity than rural migrants. Those employed in agriculture are least acquainted with social information and contacts, while those in skilled and service sectors are well acquainted with them. The results of fact and analysis show that 1) access to personal US networks results in an average 4.4 point advantage in occupational prestige scores over no access, and 2) utilizing institutional US networks combined with any cumulative US experience gives a migrant a 5 point advantage over a fellow migrant with identical experience level but no institutional network contacts. This is also true for institutional Mexican networks. Thus success or failure in migrating is partly due to migrants' societal infrastructure and the fact that available information and social networks are accessed and utilized differently by different migrants.     

Collecting experimental network data from interventions on critical links in workplace networks

This article describes and discusses challenges associated with interventionist network data gathering in organizational settings, with a special focus on dyadic interventions. While pointing out major risks of these approaches, we argue that collecting data in combination with dyadic network alteration methods can enable social network researchers to explore network mechanisms from a new angle and potentially benefit the members of the targeted social networks and the entire collectives, if certain research design and implementation principles are followed. We introduce a facilitated self-disclosure method for strengthening critical dyads in social networks in combination with longitudinal and retrospective network measurement. We assess the participants’ perceptions of the different stages of this process by qualitative interviews. The study illustrates that experimental network data collection includes some extra challenges in addition to the many challenges of observational network data collection but participants also reported practical benefits that would not be gained through observational network surveys alone. The results highlight the importance of early and continuous communication during the data collection process with all research participants, not just the management, and the benefits of sharing more of the preliminary results. The lessons learnt through this study can inform the design of experimental network data collection to prioritize the preferences of the participants and their benefits.     

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.     

Exploring the role of network diversity and resources in relationship to generalized trust in Norway

Several studies suggest a positive relationship between social capital and generalized trust. Employing a network understanding of social capital (Lin, 2001), this study questions which aspects of social networks may be linked with generalized trust. It investigates whether the diversity of social networks and the socio-economic status of one’s contacts are linked with generalized trust in the Norwegian, egalitarian context. The analyses examine these patterns in relationship to both kin and non-kin contacts. The study employs data from the first Norwegian survey that includes the position generator (PG). The empirical analyses show that extensive social networks are indeed linked to higher levels of generalized trust, but that this relationship is limited to non-kin contacts. Concerning the link between network resources and generalized trust, there is evidence of a more general association with generalized trust that holds when considering both kin and non-kin contacts. These results are a first step in developing a more nuanced discussion of the mechanisms associated with generalized trust and highlight the importance of employing measures that account for the homophily of networks when investigating their relationship to trust.     

At the intersection of criminal justice involvement and sexual orientation: Dynamic networks and health among a population-based sample of young Black men who have sex with men

Mass incarceration of young Black men has a significant impact on their network composition and stability that, in turn, may have major implications for health and well-being. A sub-group of young Black men with criminal justice involvement (CJI) identify as gay, bisexual or are non-identified men who have sex with men (hereafter MSM). This paper focuses on the potential effects of CJI on the composition of Black MSM social and sexual networks, their stability over time, and concomitant health and social outcomes. We use data from the UConnect study, a population-based cohort of young Black MSM 16–29 years of age (n = 618) selected using respondent-driven sampling in Chicago from 2013 to 2016. Both confidant and sexual network name generators and interpreters were administered at 9-month intervals over three waves of data collection. Ego and dyadic-level data were collected on behaviors prevalent among MSM and including factors associated with network CJI, network stability, and health outcomes. Generalized Structural Equation Models (GSEM) were utilized to determine the relationship between CJI network composition, network stability and behaviors prevalent among young Black MSM and their networks. In the UConnect cohort, 46% had at least once been detained, arrested or spent time in jail or prison. In addition, 20% of participants reported incident CJI over the study period. Respondents with a history of CJI were significantly more likely to have CJI homophily in their confidant and sexual networks. Multivariate analyses demonstrate that the association between one’s history of CJI, housing instability and drug use is partially explained by one’s network CJI. In addition, a higher prevalence of network CJI is associated with increased turnover in the confidant network, and this network instability is also related to important health and social outcomes. This analysis describes the networks of criminal justice involved men among a representative sample of young Black MSM and demonstrates the relationship between CJI network homophily, network stability and their impact on several key health and social outcomes relevant to this population.     

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.     

Non-response in social networks: The impact of different non-response treatments on the stability of blockmodels

Discerning the essential structure of social networks is a major task. Yet, social network data usually contain different types of errors, including missing data that can wreak havoc during data analyses. Blockmodeling is one technique for delineating network structure. While we know little about its vulnerability to missing data problems, it is reasonable to expect that it is vulnerable given its positional nature. We focus on actor non-response and treatments for this. We examine their impacts on blockmodeling results using simulated and real networks. A set of ‘known’ networks are used, errors due to actor non-response are introduced and are then treated in different ways. Blockmodels are fitted to these treated networks and compared to those for the known networks. The outcome indicators are the correspondence of both position memberships and identified blockmodel structures. Both the amount and type of non-response, and considered treatments, have an impact on delineated blockmodel structures.     

The Analysis of Duocentric Social Networks: A Primer

Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low‐income married couples, presenting visualizations and quantitative measures of network composition and structure.     

The ecology of social networks in four urban neighborhoods

This paper re-examines the question of the social “fabric” of urban neighborhoods on the basis of residents' personal networks. Data were collected on the number, relative intimacy, and spatial distribution of social relationships among residents of two ethnically homogenous and two ethnically heterogenous neighborhoods in a medium-sized city in the midwestern United States. The analysis focused on spatial distributions and variables associated with differences in the average number or intimacy of neighborhood network ties. Herbert Gans had predicted that in heterogenous neighborhoods residential proximity would be a less important factor in social network formation than has previously been reported for socially homogeneous residential settings (especially Festinger et al. 1950). The results from this study indicated that the effects of proximity were more, rather than less, reflected in the spatial distribution of social relationships in the ethnically heterogenous neighborhoods. The face-block was identified as an important socio-spatial unit in all four neighborhoods.     

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.     

Question-order effects in social network name generators

Social network surveys are an important tool for empirical research in a variety of fields, including the study of social capital and the evaluation of educational and social policy. A growing body of methodological research sheds light on the validity and reliability of social network survey data regarding a single relation, but much less attention has been paid to the measurement of multiplex networks and the validity of comparisons among criterion relations. In this paper, we identify ways that surveys designed to collect multiplex social network data might be vulnerable to question-order effects. We then test several hypotheses using a split-ballot experiment embedded in an online multiple name generator survey of teachers’ advice networks, collected for a study of complete networks. We conclude by discussing implications for the design of multiple name generator social network surveys.     

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.