Familial groups in social networks

Many structural definitions for social community have been proposed in attempt to characterize and further understand the structure of social relationships. Algorithms using quantitative concepts such as centrality measures, spectral methods and other clustering measures have been used to compute social communities. While these methods have had much success in extracting meaningful subgroups in social and biological (and other) networks, they do not necessarily reveal the defining structure of social attraction.     

Power and the perception of social networks

Previous work has led to divergent conclusions about how power affects the accuracy of network perceptions in groups and organizations. This paper develops and tests an argument linking higher power to less accurate network perception. Results from the first experiment showed that, relative to participants primed with high power, those primed with low power had more accurate perceptions of who was tied to whom in novel networks. The second experiment demonstrated that such differences in perceptual accuracy do not emerge for non-social relations.     

Measuring social networks cross-culturally

This paper explores the reliability and validity of a cross-cultural survey approach to network measurement using data from two ethnic groups in rural West Africa. Over a 2-week test-retest period, no significant differences in network size were detected. Network composition was less stable over the same period, particularly among peripheral versus core network members. Comparisons with support networks identified through lifecycle interviews and 24 h recall support the construct validity of the survey approach in both ethnic groups.     

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.     

Principles relating social regard to size and density of personal networks,with applications to stigma

Shared social evaluations (social regard) of individuals can have important consequences for those individuals. This paper presents basic principles relating social regard to the size and density of individuals’ networks. We suggest that more positive regard tends to be accompanied by positive interaction that encourages more social interaction. Thus, positive social regard is associated with larger personal networks. We then suggest that interaction among alters exacerbates effects of social regard, such that positive regard by a dense set of alters especially encourages interaction with that set. Consequently, positive regard is associated with denser networks. We present empirical support for our predictions and consider implications especially for stigmatized individuals, the objects of negative regard.     

Norm formation in social influence networks

I propose a mechanism of norm formation and maintenance that combines classical theory in social psychology on attitudes and social comparisons with a formal network theory of social influence. Underlying the formation of norms is the ubiquitous belief that there is a correct response for every situation and an abiding interest for persons to base their responses on these correct foundations. Given such a belief, a normative evaluation of a feeling, thought or action is likely to arise when persons perceive that their positive or negative attitudinal evaluation is shared by one or more influential others. If interpersonal agreements validate attitudes and transform attitudes into norms, then the development of a theory of norm formation may draw on extant “combinatorial” theories of consensus production that describe how shared attitudes are produced and maintained in groups. The network theory of social influence that I employ is one such combinatorial approach. An important sociological implication of this network theory is that the content of norms must be consistent with the social stratification (or more general pattern of inequality) of interpersonal influences in a group. I illustrate the theory with an analysis of Roethlisberger and Dickson’s (1939) classic observations on the Bank Wiring Observation Room.     

Centrality in social networks conceptual clarification

The intuitive background for measures of structural centrality in social networks is reviewed and existing measures are evaluated in terms of their consistency with intuitions and their interpretability.Three distinct intuitive conceptions of centrality are uncovered and existing measures are refined to embody these conceptions. Three measures are developed for each concept, one absolute and one relative measure of the centrality of positions in a network, and one reflecting the degree of centralization of the entire network. The implications of these measures for the experimental study of small groups is examined.     

Effects of missing data in social networks

We perform sensitivity analyses to assess the impact of missing data on the structural properties of social networks. The social network is conceived of as being generated by a bipartite graph, in which actors are linked together via multiple interaction contexts or affiliations. We discuss three principal missing data mechanisms: network boundary specification (non-inclusion of actors or affiliations), survey non-response, and censoring by vertex degree (fixed choice design), examining their impact on the scientific collaboration network from the Los Alamos E-print Archive as well as random bipartite graphs. The simulation results show that network boundary specification and fixed choice designs can dramatically alter estimates of network-level statistics. The observed clustering and assortativity coefficients are overestimated via omission of affiliations or fixed choice thereof, and underestimated via actor non-response, which results in inflated measurement error. We also find that social networks with multiple interaction contexts may have certain interesting properties due to the presence of overlapping cliques. In particular, assortativity by degree does not necessarily improve network robustness to random omission of nodes as predicted by current theory.     

Health and the structure of adolescent social networks

Much research has explored the role of social networks in promoting health through the provision of social support. However, little work has examined how social networks themselves may be structured by health. This article investigates the link between individuals' health and the characteristics of their social network positions. We first develop theoretical predictions for how health may influence the structure of adolescent networks. We then test these predictions using longitudinal analysis of the National Longitudinal Study of Adolescent Health (Add Health). We find important relationships between the health status of adolescents and the characteristics of the social network positions within which they are embedded. Overall we find that adolescents in poor health form smaller local networks and occupy less central global positions than their healthy peers. These results also have implications for social network research, expanding the scope of factors responsible for the network positions individuals occupy.     

Role similarity and complexity in social networks

A new concept of role similarity is presented; this definition is a generalisation of structural equivalence but is stricter than the idea of regular equivalence of White and Reitz (1983). This new definition forms a standard part of graph theory literature and as such has been well researched. Consequently a complexity measure first proposed by Mowshowitz, 1968a, Mowshowitz, 1968b, Mowshowitz, 1968c can be given a definite meaning in terms of network concepts. A new measure of structural complexity based on role similarity is also introduced.     

Sampling and estimation in large social networks

An unknown network is modelled by a directed or undirected graph having vertices of different kinds. Partial information is available concerning the vertex labels and the edge occurrences within a simple random sample of vertices. Using this information we find unbiased estimators and variance estimators of such graph parameters which can be given as dyad or triad counts. In particular, we give approximate formulae pertaining to large networks.     

Social networks and support in social work

Following the recommendations of the Barclay Report for a move on the part of social work towards supporting helping networks in the community, it is necessary to look more closely at the components of ‘social support’ and to be clearer about which social networks social workers are being asked to support. It is suggested that sociology, although criticised for its remoteness from the daily experience of the social worker, could offer through social network analysis some useful measures of the support networks of social work clients.     

The motivational foundation of social networks

The origins of motivations for network behavior are found in modern theories of early childhood development. There are two types of early motivations: safety on the one hand and efficacy on the other. Safety corresponds to and is generated by networks of cohesion, while efficacy comes about from separation and corresponds to networks with structural holes and is typical of brokerage situations. Both cohesion and brokerage are necessarily involved in any network situation as a matter of fundamental theoretical necessity, but they occur under different circumstances in individual and organizational action. Studies are reviewed that show that effective relations both within and between organizations require both cohesive bases and brokerage between otherwise not well connected units.     

Beyond interviewer effects in the standardized measurement of ego-centric networks

The effects which interviewers exert on the collection of ego-centric networks have recently come into the focus of methodological considerations. Studies consistently show that the size of networks varies depending on the interviewer. We would like to expand on this research strand by pointing to different aspects which have so far gone unremarked in the discussion. First, size is mainly analysed as a network measure which is influenced during data collection, while other common measures such as network density or composition have not received sufficient consideration. Second, large-scale surveys using face-to-face interviews usually allocate interviewers to a single sampling point. Differences between sampling points (locality effects) are attributed to interviewer effects. Hence, we disentangle the effects of the locality and interviewer. Third, the discussion on interviewer effects often follows an “actor-oriented” consideration of how data collection situations are structured by interviewers. Expanding this approach from a relational perspective, we consider the relationship between the interviewers and respondents and whether this relationship influences the collection of network data. To test our hypotheses about the influence of interviewers, the locality and the interviewer-respondent relationship on different network measures, we use data from the 2010 German General Social Survey (n = 2827 respondents, n = 220 interviewers). The multilevel analyses show that the relationship between the interviewer and the respondent is not very relevant. Furthermore, the analyses show that interviewers have an influence on the network size but not on measures of their composition. However, evidence on the prevalence of locality or interviewer effects is mixed. Finally, homophilous interviewer-respondent relationships have very little effect on network characteristics. We find evidence of training and fatigue effects on network size. However, much of the variation in network size caused by the interviewer still remains unexplained. We draw conclusions on how to organize interview situations in surveys.     

The role of the partner in social support networks in Spain

Social support influences the subject’s well-being through various mechanisms. Literature shows that the partner is one of the main sources of social support. Nevertheless, sometimes people do not ask their partners first for help. Our aim is to determine what factors (values related to the family, personal characteristics and availability of resources) influence this decision. We use Spanish representative samples from International Social Survey Programme (2001) and Spain’s Center for Sociological Research (2010). Data show that family solidarity is widespread in Spanish society. The determinants for not turning first to the partner are the availability and frequent contact with immediate kin, whereas family values and personal characteristics are less relevant.     

Predictors of accuracy in perceiving informal social networks

One's ability to accurately perceive the existence of informal social networks, referred to as cognitive accuracy, has recently been shown to play an important role in explaining various social phenomena. This paper addresses the research question of what predicts cognitive accuracy by developing a simple theory which links one's accuracy to the amount of information one exchanges with co-workers. To test the predictions of my theory, I analyze friendship and advice network data from a small entrepreneurial firm. The results of the analysis show that predictors of accuracy tend to be workers' degree centrality in the friendship or advice network and demographic and social distances between workers.     

The role of social networks in the care of young children

SUMMARY. From birth, children develop, play and work within extensive social networks; yet little systematic research has been carried out to examine these relationships. This article summarises findings about the network relationships of young children from a study undertaken to explore the diverse ways in which their parents made childcare and babysitting arrangements. The different experiences of the children were found to be closely linked to parental beliefs and values, as well as the nature of the local neighbourhoods and network patterns. They were also associated with varied evolutionary sequences in the social relationships of both adults and children