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.     

The distant core: social solidarity,social distance and interpersonal ties in core–periphery structures

We examine three hypotheses at the foundation of theories concerned with the organization of social space and social solidarity in differentiated groups. The most important of these hypotheses is that interpersonal ties between actors in different positions of a social structure foster social solidarity; however, the theories are silent on the question of whether this effect of interpersonal ties is maintained regardless of the distance that separates the positions of two actors in the group’s social space. In addition, the current zeitgeist on the organization of social space hypothesizes that interpersonal solidarity and ties are negatively associated with the distance that separates the positions of actors in social space. Although interpersonal ties foster solidarity, social distance reduces the likelihood of interpersonal ties and solidarity. Our evidence suggests unqualified support only for the first hypothesis. Surprisingly, the expected negative effects of social distance on interpersonal ties and solidarity appear to be properties of particular forms of social organization and are not ubiquitous implications of social differentiation. These negative effects are more or less pronounced (even reversible) in core–periphery structures depending upon the distance between the core and peripheral positions in the social space of the group.     

Centrality and power revisited: actor success in group decision making

For many years, network analysts viewed positional centrality as a source of social power. More recently, laboratory studies of exchange networks have called the centrality–power link into question: under zero-sum exchange conditions, the ability of certain actors to directly exploit others has been found to account for power independent of actors' centrality. But most observers believe that in non-zero-sum communication networks, centrality should positively affect power. In this study we examine the effect of centrality on power in a communication network involving group voting on political issues. Using a model in which actors' votes are determined by the strength of their initial positions and the social pressures to which they are subjected, we conduct computer simulations to examine the extent to which actors in various network positions achieve favorable political outcomes. Our findings indicate that the link between centrality and power is highly contingent on the structure of the network. In networks with a central actor and an odd number of subgroups, central actors fail to dominate. In fact, in these networks, when peripheral actors are able to directly influence one another, the central actor becomes the least powerful in the network. In networks with a central actor and an even number of subgroups, however, the central actor dominates even in situations with connected peripherals. The highly contingent effect of centrality on power accords with the findings of exchange theorists who have studied power under zero-sum conditions. This raises questions about the nature of the distinction between communication and exchange networks.     

Social networks and innovation adoption: A look at burt's use of structural equivalence

This paper examines Burt's 1982 model of innovation adoption based on an application of structural equivalence. The proposition that two structurally equivalent actors will adopt an innovation at approximately the same time is explored. The diffusion of two innovations through a network of commercial fishermen provides the basis for an empirical test. Tentative support for this proposition is found, particularly if the effects of information availability, economic competition, and the appropriateness of the innovation are taken into account.     

The Cohesiveness of Blocks In Social Networks: Node Connectivity and Conditional Density

This study shows several ways that formal graph theoretic statements map patterns of network ties into substantive hypotheses about social cohesion. If network cohesion is enhanced by multiple connections between members of a group, for example, then the higher the global minimum of the number of independent paths that connect every pair of nodes in the network, the higher the social cohesion. The cohesiveness of a group is also measured by the extent to which it is not disconnected by removal of 1, 2, 3,..., k actors. Menger's Theorem proves that these two measures are equivalent. Within this graph theoretic framework, we evaluate various concepts of cohesion and establish the validity of a pair of related measures: 1. Connectivity—the minimum number k of its actors whose removal would not allow the group to remain connected or would reduce the group to but a single member—measures the social cohesion of a group at a general level. 2. Conditional density measures cohesion on a finer scale as a proportion of ties beyond that required for connectivity k over the number of ties that would force it to k + 1.
Calibrated for successive values of k, these two measures combine into an aggregate measure of social cohesion, suitable for both small- and large-scale network studies. Using these measures to define the core of a new methodology of cohesive blocking, we offer hypotheses about the consequences of cohesive blocks for social groups and their members, and explore empirical examples that illustrate the significance, theoretical relevance, and predictiveness of cohesive blocking in a variety of substantively important applications in sociology.     

Network knowledge and the use of power

Complementing recent work on the effects of power on network perceptions, we offer a theory specifying how knowledge of network structures and exchange processes differentially affect the use of power by advantaged and disadvantaged positions. We argue that under certain conditions, network knowledge is beneficial to occupants of low-power positions, but not to occupants of high-power positions. Any low-power actor can benefit from having superior information, but if all low-power actors have equally sound knowledge, then all are worse off—a type of social trap. We tested these arguments by manipulating power and the availability of information on network structure and exchange processes in an experimental exchange network setting. The results were supportive.     

Preference intensity representation: strategic overstating in large elections

If voters vote strategically, is it useful to offer them the possibility of expressing nuanced opinions, or would they always overstate the intensity of their preferences? For additive voting rules, say that a ballot is extremal if it is neither abstention-like nor can be expressed as a mixture of the available ballots. We give a sufficient condition for strategic equivalence: if two rules share the same set of extremal ballots (up to an homothetic transformation), they are strategically equivalent in large elections. This condition is also necessary for the strategic equivalence of positional rules. These results do not hold for small electorates.     

Positions,Roles, and Dependencies in a Community Interorganization System*

This study focuses on community structure as a network of interorganizational linkages, with an eye toward (1) generating new conceptual schemes to study the community as a social network and (2) developing a methodology to measure new dimensions of community structure. An analysis of structurally equivalent roles is performed in two communities for three organizational resource networks: money, information, and moral support. Global dependencies on resource generator, consumer, and transmitter roles for the money network are analyzed using loglinear models. Local dependencies within the money network are also examined. Finally, the study examines the perceived influence of organizations in community affairs as a function of the organizations' global positions within the community network.     

Mental Maps: Social Networks and the Language of Critical Reviews

This study uses network analysis to examine the correspondence, based on Bourdieu's theory of cultural production, between artists'positions in a structure of social relations and the critics'conceptions of their work. Shared gallery memberships among fine art photographers yield person-by-person matrices that are partitioned into structurally equivalent blocks. Three types of actors emerge: "stars" who have large loose-knit networks of bridge ties, "invisible collegians" who inhabit small dense cliques, and "stragglers" who have difficulty maintaining any sort of foothold in the network. Critical reviews of the photographers in the population are then analyzed for stylistic references, and the photographers are matched to stylistic categories. A match emerges between the types of networks and the stylistic perceptions of the critics. "Stars" are categorized with a wide variety of stylistic terms, often contradictory in nature. "Invisible collegians" and "stragglers" are routinely fit into one stylistic camp or another. Multiplying the person by style matrix by its transpose yields a person-by-person matrix of perceived shared stylistic affinity. "Stars" in this matrix have higher scores of both degree and "betweenness" centrality.     

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.     

Centrality in affiliation networks

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

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.     

Comparison of methods for positional analysis: Structural and general equivalences

This paper explores the conceptualization and measurement of social position in relational data. It is argued that social positions are evidenced in the interactions among individuals, which are encoded in measured social relations. Given a set of measured relations the task is to reveal social positions which consist of groups of individuals wth similar patterns of relations. Methods based on two alternative approaches are discussed. The first set of approaches is based on structural equivalence, and locates groups of similar individuals based on the extent to which they share identical ties with identical others. A second set of approaches, here called general equivalences, locates groups of similar individuals based on their sharing of “types” of ties with “types” of others. Procedures based on these different approaches are described and applied to actual data and to a constructed example. Results suggest that these different approaches identify different kinds of social groups. It is argued that structural equivalence is an unsuitable basis for analysis of relational data if the goal is detection of social positions.     

Movement without mobility: Adolescent status hierarchies and the contextual limits of cumulative advantage

This paper develops a theory of interpersonal status hierarchies that builds on and challenges traditional models of cumulative advantage. Cumulative advantage models predict stability in interpersonal status hierarchies, where status is defined by asymmetries in social relationships. According to strict cumulative advantage, initial status differences are exaggerated over time, making upward or downward mobility unlikely. We argue that interpersonal status hierarchies are instead quite fluid, with individuals regularly moving up or down the hierarchy. Individual status gains do not, however, disrupt the status order as the upwardly mobile are often pulled back to their original positions. This drag of the past generates the same long run status outcomes as cumulative advantage models, but through very different means: sustained upward mobility is rare because the upwardly mobile fail to maintain their status gains, and not because initial gains are impossible. More generally, the effect of the past limits sustained mobility in most, but not all, status hierarchies, and we expect sustained mobility where ties are stable and the expectations for reciprocity are low. We test our model using longitudinal data on adolescents, finding strong support for the theory. We end the paper with a reflexive discussion about measurement error, hypothesis testing, and “messy” longitudinal network data.     

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.     

Political Participation of Local Publics in the Unemployment Field: A Comparison of Lyon and Turin

This article focuses on political participation of local publics in the unemployment field, examining networks of collective actors in Lyon and Turin. Our main question is: Is the participation of local publics fostered under conditions of more developed governance that increases bottom-up access (formal or informal) to elites and institutions in the policy domain? Drawing upon the most recent developments in literatures on social movement theory, governance and network analysis, this article discusses the main variations in terms of political participation of local publics in Lyon and Turin. It then enquires into the main explanatory factors accounting for these variations, thus showing that the openness of governance does influence the level of political participation of local publics. The main argument is that in an open context participation is low, while in a closed (or underdeveloped) context local publics participate more, with differential access to decision-making according to their resources.     

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.     

Introduction to stochastic actor-based models for network dynamics

Stochastic actor-based models are models for network dynamics that can represent a wide variety of influences on network change, and allow to estimate parameters expressing such influences, and test corresponding hypotheses. The nodes in the network represent social actors, and the collection of ties represents a social relation. The assumptions posit that the network evolves as a stochastic process ‘driven by the actors’, i.e., the model lends itself especially for representing theories about how actors change their outgoing ties. The probabilities of tie changes are in part endogenously determined, i.e., as a function of the current network structure itself, and in part exogenously, as a function of characteristics of the nodes (‘actor covariates’) and of characteristics of pairs of nodes (‘dyadic covariates’). In an extended form, stochastic actor-based models can be used to analyze longitudinal data on social networks jointly with changing attributes of the actors: dynamics of networks and behavior.     

Knowledge and networks: An experimental test of how network knowledge affects coordination

Scholars in the social sciences use network theory to study a range of collective action problems. Often the goal is to identify how the structure of the network affects efforts to coordinate or cooperate, and research suggests that adding connections to a network can improve the performance of groups faced with such tasks. On the other hand, theory and empirics also suggest that additional connections can degrade the performance of a network. If connections can have negative effects then it is important to consider if there are alternatives to adding connections to a network that can also improve network performance. Because a primary function of connections in a network is to disseminate information, providing individuals with more information about the network may act as a substitute for adding connections to a network. We test experimentally whether providing subjects with more information about the structure of networks can improve coordination. We find that a more complete view of the network leads to faster coordination, but the magnitude of this effect depends on network structure. These results suggest that changing what actors know about a network can improve outcomes without having to add connections that may impede overall performance.     

Jaccard-Spline index of structural proximity in contact networks

Network analysts are increasingly being called upon to apply their expertise to groups for which the only available or reliable data is a contact network. With no opportunity to gather additional data, the merits of such applications depend on empirical studies that validate the employment of structural constructs based on contact networks. Fortunately, we possess such studies in abundance. One of the strongest research traditions in social network analysis is the development of formal constructs that may be employed in analyses of networks. I suggest that greater insight into predictive success of network constructs may be acquired by addressing the following question: what features of the contact network in which a dyad is situated allow the prediction of other relations with an accuracy that validates the imputation of the latter given data on the former? In this article, I present findings on the structural contexts of dyads in contact networks and the relationship of these contexts with two fundamental forms of cohesive cognitive relations—accorded interpersonal influence and perceived interpersonal agreement. Based on these findings, I formalize a measure of structural proximity in contact networks with values that correspond to the conditional probabilities of these two forms of cohesive cognitive relations. The substantive settings of this analysis are policy groups with members who are embedded in contact structures based on regular interpersonal communication on policy issues and cognitive structures based on perceived interpersonal agreement and accorded interpersonal influence.