Goal specific social capital and job satisfaction: Effects of different types of networks on instrumental and social aspects of work

This paper addresses the question “To what extent can job satisfaction be explained as the revenue of social capital?” By conceiving someone’s social network as social capital we specify conditions under which social ties do lead to job satisfaction. We inquire into the idea of goal specificity of social capital, which implies that a network with a given structure and content will have different impacts on various aspects of job satisfaction. If the content of the ties and the structure of the network at the job engender material well-being or produce social approval, satisfaction with the corresponding job aspects increases. Data were collected in 1993 using written questionnaires in two Dutch governmental agencies, one with 32 and the other with 44 employees. These workers’ networks were charted using nine name-generating questions.Social capital, it turns out, is not an all-purpose good but one that is goal specific, even within a single domain of life such as work. Three effects stand out: First, the structure of the network and the content of the ties do matter. Networks of strategic, work-related ties promote an employee’s satisfaction with instrumental aspects of the job, like income, security, and career opportunities. Second, closed networks of identity-based solidarity ties improve an employee’s satisfaction with social aspects of the job, like the general social climate at work and cooperation with management and colleagues. Third, a network with a bow–tie structure (i.e., where a focal actor is the link between two or more mutually exclusive cliques) generally has strong negative effects on satisfaction with the social side of the job; although a bow–tie type network of trusting ties does increase satisfaction with the social side. This implies that Krackhardt’s hypothesis on the unpleasant feelings produced by bow–tie type networks has to be specified for the content of the ties that constitute such a network. The most important conclusion of our analysis is that goal specificity of social capital has implications for both structure and content of social networks. Achievement of a particular goal, such as satisfaction at work, requires not only networks of a certain structure or ties with a particular content, but specifically structured networks of ties with a particular content.     

Dense core model for cohesive subgraph discovery

Discovery of cohesive subgraphs is an important issue in social network analysis. As representative cohesive subgraphs, pseudo cliques have been developed by relaxing the perfection of cliques. By enumerating pseudo clique subgraphs, we can find some structures of interest such as a star-like structure. However, a little more complicated structures such as a core/periphery structure is still hard to be found by them. Therefore, we propose a novel pseudo clique called ρ-dense core and show the connection with the other pseudo cliques. Moreover, we show that a set of ρ-dense core subgraphs gives an optimal solution in a graph partitioning problem. Several experiments on real-life networks demonstrated the effectiveness for cohesive subgraph discovery.     

Perspective-taking and memory capacity predict social network size

Human social networks typically consist of a hierarchically organized series of grouping levels. There is, however, considerable variation between individuals in the sizes of any given network layer. We test between two possible factors (memory capacity and theory of mind) that might limit the size of two different levels within human social networks (support cliques and sympathy groups). We show that the size of an individual's support clique (the number of individual's in the innermost circle of friends) is better explained by individual differences in social cognition (mentalising skills). However, the size of the sympathy group (the most frequent social partners) is better explained by individual's performance on memory tasks.     

A message-focused measurement of the communication dimension of social capital: Revealing shared meaning in a network of relationships

This study integrates two theoretically driven methods—network analysis and fantasy theme analysis—to present a message-focused operationalization for the communication dimension of social capital. The results find empirical support for scholars’ theorizing that public relations-facilitated messages cultivate shared meaning and foster social capital. The relationship between shared meaning and social capital was especially evident in network subgroups (cliques). This article contributes to social capital theory building by focusing on the meaning making process that strengthens social capital in networks. Public relations practitioners’ communicative roles in social capital cultivation are made evident with a message-focused measurement.     

Class inequalities in access to social capital in the metropolitan area of Buenos Aires

this paper analyzes social class inequalities in access to social capital. Quantitative methodology was used with data from the PI-Clases “Reproduction and social mobility in family trajectories and life courses” survey, conducted in the Metropolitan Area of Buenos Aires in 2015 (n = 1065). Social capital measures where derived from the Position Generator (Lin, 2001) to identify the volume, status and range of the respondent’s networks. Results show that there are class inequalities in access to social capital in terms of the number of contacts, mean status of contacts, range of contact’s status and highest status of contacts. Also, the working class is more heterogeneous in its access to social capital, suggesting it has a sector that has network ties with people from the middle class and a sector with lower social capital. The observed trend is of gradational differences between class strata, with more marked inequalities between the service, intermediate and working class, but with fluid class boundaries without social segregation. Also, social capital is conditioned by intergenerational mobility trajectory, showing a trend of elasticity in the class composition of social relationships. The upwardly mobile can increase their access to social capital but don’t reach the same level as the intergenerationally stable, while the downwardly mobile retain some social capital from their class origins.     

Social networks and getting a home: Do contacts matter?

Under what conditions does one find a new home via one's social network? Does the way in which a house is acquired affect how satisfied one is with the house? We formulate hypotheses on the characteristics of personal networks, the context of the move and their effect on those who attain a house through informal channels and how satisfied they are with the new home. We use a representative dataset from the Netherlands (the Survey of the Social Networks of the Dutch, SSND, n = 1007) to test our arguments. Our results show that buyers with more diverse social networks and renters with larger social networks are more likely to find their home via social contacts. However, finding a home through an informal channel does not enhance their satisfaction with the house that is found.     

The roles of human capital and social capital in the economic integration of new arrivals from Mainland China to Hong Kong

Although it has been hypothesized in the literature that both human capital and social capital are important for the economic performance of new immigrants, few studies have examined these relationships empirically, especially in understudied populations such as Chinese populations. This study simultaneously examines the roles of human capital and social capital in the economic integration of new arrivals from Mainland China to Hong Kong, using a random sample of immigrants. In the early stage of immigration (less than 6 months after arrival), we find little support for the presumed positive effects of both human capital and social capital on employment status among new arrivals in Hong Kong. Follow-up studies are underway to investigate the dynamic relationship between social capital and economic integration in this group of new arrivals, and whether social capital, especially friendship networks, plays a more important role in the economic integration of new immigrants 1 or 2 years after arrival.     

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.     

Statistical power of the social network autocorrelation model

The network autocorrelation model has become an increasingly popular tool for conducting social network analysis. More and more researchers, however, have documented evidence of a systematic negative bias in the estimation of the network effect (ρ). In this paper, we take a different approach to the problem by investigating conditions under which, despite the underestimation bias, a network effect can still be detected by the network autocorrelation model. Using simulations, we find that moderately-sized network effects (e.g., ρ = .3) are still often detectable in modest-sized networks (i.e., 40 or more nodes). Analyses reveal that statistical power is primarily a nonlinear function of network effect size (ρ) and network size (N), although both of these factors can interact with network density and network structure to impair power under certain rare conditions. We conclude by discussing implications of these findings and guidelines for users of the autocorrelation model.     

From attitudes to social networks: National gender-role attitudes and gender differences in late-life social relationships

Studies often find gender differences in social networks in later life, but are these findings universal, or do they differ in various cultural contexts? To address this research gap, the current study examines the association between gender differences in social relationships and country-level gender-role attitudes. We combined data from the Survey of Health, Ageing and Retirement in Europe (SHARE) of individuals aged 50 years and older with country-level data on gender-role attitudes from the European Values Survey (EVS) for 15 European countries. We estimated a series of multivariate hierarchical regression models that predicted the size of the personal social network, its emotional closeness, and the proportion of the spouse, children, and friends in the network. The results indicated gender differences in social network characteristics. Women reported larger social networks and were more likely to have larger proportions of children and friends but smaller proportions of the spouse in their social networks. The magnitude of gender differences was associated with country-level gender-role attitudes. In countries with more egalitarian gender-role attitudes, women had larger networks with a larger proportion of friends compared to men. In countries with more traditional gender-role attitudes, women had larger proportions of their children and spouse in their social networks and had emotionally closer networks. Our findings suggest that the societal context and opportunity structures for social interactions play an important role in shaping the structure of women’s and men’s social relationships in later life.     

Fostering social capital in an international multi-stakeholder issue network

Scholars have theorized that public relations contributes to societies and communities by bringing attention to pressing public issues and fostering social capital in civil society networks. However, the extant research has studied civil society networks of NGOs, donors, and the media in transitional countries. This study extends the public relations model of civil society in two ways. First, it broadens the scope to an international context. Second, it draws from the multi-stakeholder issue network perspective to conceptualize a civil society network as a space where stakeholders of an issue mix their interests as they collectively address a pressing public issue. The literature on international and multi-stakeholder networks suggest that the international scope and the mixing of interests across sectors may restrict the production of social capital. The results from the social network analysis suggests that the mixing of interests across sectoral and geopolitical boundaries did not restrict the production of social capital. Rather, the patterns of the relationships among those on the core and those on the periphery of the network restricted the production of social capital. Such finding demonstrates how public relations’ functions like relationship building can have profound influences on social capital and civil society networks. The implications for public relations theorizing and research are discussed.     

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.     

Humanitarian Interorganizational Information Exchange Network: How Do Clique Structures Impact Network Effectiveness?

Humanitarian information coordination and sharing continue to challenge the international community. Interorganizational networks are believed to be a way to improve coordination and collaboration among humanitarian organizations. Although researchers have devoted a considerable amount of time exploring the influence of network structure on network performance and effectiveness, little work has been done in the humanitarian relief field. We use the theoretical lens of social network to investigate the relationship between network cliques and network effectiveness. Data were collected through multiple sources among members of GlobalSympoNet, a community of humanitarian organizations engaged in humanitarian information management and exchange. Our findings suggest that, similar to the public health service delivery sector, network effectiveness can be explained by network integration and network cliques in the humanitarian relief field. We discuss these findings and provide some implications of our research in designing interorganizational networks within the humanitarian relief field.     

Social Capital and Neighborhood Poverty

ABSTRACT

Research indicates that concentrated neighborhood poverty has numerous detrimental effects on the health and well-being of individuals, families, and communities. The term “neighborhood effects” has been used to describe the interaction between socioeconomic disadvantage and social problems at the neighborhood level. Social capital theory, defined broadly as social networks characterized by trust and reciprocity represents one prominent explanation for the phenomenon of neighborhood effects. Within poor neighborhoods, it is theorized that socioeconomic characteristics of the neighborhood foster inadequate social capital and it is this low level of social capital that leads to the phenomenon of neighborhood effects. In order to explore the utility of social capital theory in explaining neighborhood effects, this paper argues for an ecologically-grounded model of social capital that allows for the different ways in which social capital operates within different types of neighborhoods. Implications for social work practice, policy and education are discussed.     

Estimating network structure via random sampling: Cognitive social structures and the adaptive threshold method

This paper introduces and tests a novel methodology for measuring networks. Rather than collecting data to observe a network or several networks in full, which is typically costly or impossible, we randomly sample a portion of individuals in the network and estimate the network based on the sampled individuals’ perceptions on all possible ties. We find the methodology produces accurate estimates of social structure and network level indices in five different datasets. In order to illustrate the performance of our approach we compare its results with the traditional roster and ego network methods of data collection. Across all five datasets, our methodology outperforms these standard social network data collection methods. We offer ideas on applications of our methodology, and find it especially promising in cross-network settings.     

Social capital,guanxi and political influence in Chinese government relations

Social capital has emerged as a promising theoretical approach to understanding political influence in the public relations literature. However, the rationale of using social capital to influence corporate government relations in authoritarian societies is indistinct. To remedy this, we integrate Bourdieu’s (1986) and Lin’s (2001) social capital theories to explore how applying a variant form of social capital (e.g., guanxi) might shape corporate government relations in authoritarian China. A multi-method, qualitative approach was employed involving 44 interviews, participant observation and document review. The findings highlighted an underexamined “vertical” dimension of social capital (i.e., links with authority in a hierarchy), which enables corporations to exercise agency over the pre-existing and often vague regulatory environment. This study adds a new perspective to social capital with hierarchical guanxi that enriches our understanding of guanxi-based political influence in Chinese corporate government relations.     

A comparative study of social network models: Network evolution models and nodal attribute models

This paper reviews, classifies and compares recent models for social networks that have mainly been published within the physics-oriented complex networks literature. The models fall into two categories: those in which the addition of new links is dependent on the (typically local) network structure (network evolution models, NEMs), and those in which links are generated based only on nodal attributes (nodal attribute models, NAMs). An exponential random graph model (ERGM) with structural dependencies is included for comparison. We fit models from each of these categories to two empirical acquaintance networks with respect to basic network properties. We compare higher order structures in the resulting networks with those in the data, with the aim of determining which models produce the most realistic network structure with respect to degree distributions, assortativity, clustering spectra, geodesic path distributions, and community structure (subgroups with dense internal connections). We find that the nodal attribute models successfully produce assortative networks and very clear community structure. However, they generate unrealistic clustering spectra and peaked degree distributions that do not match empirical data on large social networks. On the other hand, many of the network evolution models produce degree distributions and clustering spectra that agree more closely with data. They also generate assortative networks and community structure, although often not to the same extent as in the data. The ERGM model, which turned out to be near-degenerate in the parameter region best fitting our data, produces the weakest community structure.     

Social capital and public goods

Previous literature suggests positive relationships between social capital, pro-social behavior and subsequent economic development. We analyze the relationship between social networks and trust (two measures of social capital) and self-reported charitable contributions of time and/or money (pro-social behavior) using data collected from two ethnically distinct, low-income neighborhoods. We find that large social networks are positively related to charitable contributions, but that the effects of trust are less robust. We also find that social networks that are more geographically dispersed tend to be larger. Our results indicate that the social capital in a neighborhood is more important than ethnicity, ethnic diversity, or other demographic information in understanding public goods contributions.     

The Exclusiveness of the Political Field: Networks and political mobilization

This paper applies social network analysis to three case study social movement organizations based in the north of England: a local Labour Party branch, an environmental group, and a conservation group. Using a postal survey of members, we chart the extent of ties between members of these three groups, indicating how each group has its own internal social dynamics and characteristics that are related to the nature of the movement organizations themselves. We explore how the network structures interrelate with the socio-demographic structure of the membership of the three organizations, and we show there are important differences in the way that core members of the three organizations are recruited compared to those who are either peripheral or isolated. Our paper is the first to analyse the networks of whole populations of case study organizations in the UK, and can therefore be read as developing the potential of social network analysis for case study research and for understanding social movements. Analytically we argue it is important to distinguish two different types of ways that networks are important. They can be seen as offering resources for mobilization, or they can be seen as providing a means of integrating particular types of individuals into organizations. It is this latter sense that offers a more fundamental role for network analysis, and we argue that it offers an important way of developing insights from resource mobilization theory by relating them to Bourdieu's provocative arguments regarding the exclusiveness of the political field.     

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.