Network Analysts Research Articles

Introduction to Focus: The Affective Turn

Page 3 September–October 2008 The Affective Turn Introduction to Focus: Aaron D. Chandler, Focus Editor If we need evidence that emotions, understood in their broadest sense, continue to pose a serious problem to our stand-by interpretive frameworks, consider Hillary Clinton’s teary moment in January of this year. Responding to a New Hampshire voter’s question about her campaigning fortitude, Clinton turned unexpectedly demonstrative and answered with a broken voice and watery eyes. “You know, this is very personal for me,” she confided, “it’s not just political…it’s not just public.” This expression of “personal” feeling would become quite “public” and “political” indeed, when within hours video of the incident was being unremittingly replayed on every news outlet and scrutinized by millions onYouTube. Many in the media took the crying as a symptom, and though there was only modest agreement about the disease, the prognosis was emphatically grave. Television pundits and putative experts often shot off their diagnoses in the form of loaded questions: Was Hillary herself becoming unglued? Had the Clinton machine simply malfunctioned? Would this be taken as proof of a basic feminine fragility unsuited to the demands of presidential leadership? The commentariat consulted itself and agreed that these tears marked the end of a political dynasty, even as many New Hampshirites spoke quietly, though uncertainly, of a newfound compassion for the candidate. Two days later, Clinton won New Hampshire handily, and a second fusillade of questions followed. How had everyone been so mistaken? Had her tears alone moved the electorate? Would these televised tears work against her in the general election against a more hawkish rival? Hidden beneath these difficulties was another: could a small pang of feeling, so palpably unbidden and contingent, really shift the course of an historic nomination? And opposed to this, yet another question lurked: had this sob been nothing more than a performance—an act of political cunning? Was “The Cry Heard ’Round the World” a case of proverbial crocodile tears? In brief, for a gusty week or two, water-cooler denizens and network analysts puzzled and opined over how “private” feeling could go so public so fast while “public” feeling could remain so secretive. Hillary herself alluded to the tearful moment in her victory speech, declaring that the state had “helped her find her voice.” Esteemed columnists wrote think pieces citing the damp cheeks of politicians past—Ed Muskie in 1972, Pat Schroeder in 1987—but nothing seemed to solve the problem that the meaning of a spontaneous, selfevident emotional expression was not equally natural and self-evident. A new spate of scholarly studies in affect and emotion may help to illuminate this kind of problem or perhaps explain why we distinguish it as a problem in the first place. This special “Focus” of ABR considers some of the most interesting recent contributions to the critical conversation about affect, emotion, and their place in cultures of the present and past. Still, one must begin by noting that this critical conversation itself became heated well over a decade ago in fields as diverse as neurobiology, anthropology, psychology, sociology, as well as in cultural and literary theory. One could go further back, of course, given that opinion-makers have fretted for centuries over the hows and whys of feeling, public and otherwise. Though one would never guess it, given their assorted outbursts, Clinton, Barack Obama, and John McCain are all members of the legislative body George Washington described as the saucer in which the tea of popular passions cooled. Indeed, this unrest over other people’s feelings goes much further back—through the pages of Immanuel Kant, Thomas Hobbes, Plato—as far as we might cognition and emotion not as polar opposites but rather as closely related elements in our manner of being, as if deliberative reason were the nimble forefingers of cognition and emotion the clinching thumb. Getting rid of the old reason/emotion opposition was philosopher Ronald de Sousa’s primary aim in The Rationality of the Emotions (1987). Similarly, neurobiologist Antonio R. Damasio, in his popular Descartes’ Error (1994) and The Feeling of What Happens (1999), argues that thinking and feeling are indissolubly linked; neuroscientist Joseph...

Faster than Smoke? More Blinding than Mirrors?

Version 3.0 of the cable television industry's data transport standard, Data over Cable Service Interface Specifications (DOCSIS), might speed the time to download anything from a text file to a movie to 160 megabits per second. Even if the technology's theoretical maximum speed isn't commercially realistic, its demonstration at the May 2007 annual Cable Show in Las Vegas has network strategists and analysts wondering how users and competitors will react.

The structure of norms and relations in patronage systems

Patronage systems are composed of a social relation (between patron and client), the norms associated with this relation (support, defend, not attack), and network-formation rules (governing the creation of patronage ties). Actors in a patronage system face moral dilemmas when they become obligated to fight on both sides of a conflict, and patronage systems are normatively consistent when these dilemmas can never arise. This paper examines the structure of normatively consistent patronage systems, exploring the logical relationships among norms and between norms and network structure. The paper illustrates how sociologically relevant concerns from deontic logic can be incorporated into network analysis using algebraic methods familiar to network analysts.

Social capital and information science research

AbstractThe concept of social capital has become a popular area of research in many social science fields, including public policy, political science, economics, community development, sociology, anthropology, and education. Increasingly, it has been used as the conceptual framework for research in the area of information studies including such topics as knowledge integration (Bhandar, Pan & Tan, 2007), knowledge sharing (Huysman & Wulf, 2006), access to information by the homeless (Hersberger, 2003), community informatics (Williams and Durrance, in press), and information seeking behavior (Johnson, in press). The concept has an ideological foundation in the theories of Pierre Bourdieu (1980), with two divergent approaches to its study emerging during the last two decades: one focusing on social capital as a collective asset and the other regarding it as an individual asset. The main proponent of the first approach is political scientist Robert Putnam who defines social capital as inhering in the “dense networks of social interaction” which foster “sturdy norms of generalized reciprocity and encourage the emergence of social trust” (Putnam, 1995, p. 66). Social network analysts, on the other hand, view social capital as resources to which individuals have access through their social relationships. Nan Lin, who is the main proponent of this approach, defines social capital as “resources embedded in a social structure which are accessed and/or mobilized in purposive actions” (Lin, 2001a, p. 12). While the concept of social capital may be operationalized differently depending on the point of view of the researcher, its value to information science research is in providing a framework within which to understand the relationship between social structure and information access.Participants in this panel will discuss social capital from various vantage points, including the role of social capital in solidifying power relationships, the effect of recent government policies on reducing social capital, and the relationship between social capital and the use of libraries and information technology. The intent of the panel is to clarify the meaning(s) of social capital and to demonstrate how the concept may be used in information science research.

SNEM: a new approach to evaluate terminal pair reliability of communication networks

PurposeThis paper proposes a new approach source node exclusion method (SNEM) to evaluate terminal pair reliability of complex communication networks.Design/methodology/approachThe proposed approach breaks a non‐series‐parallel network to obtain its sub‐networks by excluding the source node from rest of the network. The reliabilities of these sub‐networks are thereafter computed by first applying the series‐parallel‐reductions to it and if any sub‐network results into another non‐series‐parallel network then it is solved by the recursive application of SNEM.FindingsThe proposed method has been applied on a variety of network and found to be quite simple, robust, and fast for terminal pair reliability evaluation of large and complex networks.Practical implicationsThe proposed approach is quite simple in application and applicable to any general networks, i.e. directed and undirected. The method does not require any prior information such as path (or cut) sets of the network and their pre‐processing thereafter or perform complex tests on networks to match a predefined criterion.Originality/valueThe proposed approach provides an easy to develop and easy to use tool to determine terminal pair reliability of a communication network. The approach is particularly useful for communication network designer and analysts.

Regular equivalence and dynamic logic

This paper describes a precise linguistic counterpart to the notion of a regular equivalence relation on a social network. That is, a formal language of position terms is defined with the property that on finite networks, two actors are regularly equivalent if and only if they cannot be distinguished by a position term. The paper also contains an exact characterization of the set of complex relations which are preserved under regular equivalences. The results presented here are known from logic and computer science, in which the mentioned language is called dynamic logic. The aim of the paper is to make these results available to social network analysts and explain why they are of interest to them.

Social Networks of the Marginal Young: A Study of Young People's Social Exclusion in Finland

It has been argued by many social network analysts that community ties and social support provided by them still continue to flourish in the late-modern societies, despite the general fear of the loss of community as a result of such large-scale social changes as urbanization, individualization and globalization. This article examines the role of community ties in the lives of young people who hold marginal positions in the Finnish labour market and are considered as being at risk of social exclusion. Based on survey data (n= 144) collected from young people aged 18-27 years, the article explores whether young people's exclusion from paid employment also leads to their exclusion from all significant social networks, as has often been assumed. It will be argued that the link is not automatic. Instead, the community ties continue to flourish and provide social support to young people also at the margins of society.

Determining groups from the clique structure in large social networks

Abstract Ethnographers have traditionally defined human groups as disjoint collections of individuals who are linked to each other by regular interaction, shared perceptions and affective ties. They are internally differentiated: some members occupy a central position in the group, others are on the periphery or somewhere in between. This way of characterising a group is intuitive to seasoned observers but social network analysts seek a more systematic method for determining groups. Freeman [Freeman, L.C., 1996. Cliques, Galois lattices, and the structure of human social groups, Social Networks 18, 173–187.] describes a formal model based on the concept of overlapping social network cliques. Freeman's analysis produces results that are consistent with ethnographic results but his technique is not easily implemented for very large data sets. This paper describes two algorithms based on Freeman's clique–lattice analysis. The first implements his technique exactly; the second is a modification that exploits the clique structure, thereby enabling the analysis of large complex networks. We apply both algorithms to a real data set and compare the results.

Handbook of emerging communications technologies: the next decade

Communication technologies change the way we live our lives-the ways we communicate and share information, the news, and our entertainment. The new millennium promises to bring some of the most volatile activity in the history of communications, as we continue to be bombarded by new standards and technologies. The near frenzy of corporate mergers and acquisitions accelerates technological development and can provide hints of what is to come. With the rapid appearance of new protocols, standards, and tools, it becomes increasingly difficult -and increasingly important-for communications professionals to remain up-to-date on new and emerging technologies.The Handbook of Emerging Communications Technologies: The Next Decade fills this gap. Until now, information on many of its topics, such as Multiprotocol over ATM, IP Multicasting, and RSVP, existed only as fragmented articles on the Internet or as complex feature specifications. In this landmark volume, 18 leading authorities each tackle one of the cutting edge technologies destined to shape the future. Each chapterDescribes a technology and any standards on which it is basedDiscusses its impact on the communications field Forecasts its future directionDeveloped primarily for telecommunications specialists network managers, developers, and analysts, the Handbook of Emerging Communications Technologies: The Next Decade, offers the opportunity to acquire a deeper understanding of future technologies necessary to remaining current, and serves as a valuable reference guide for corporate executives, planners, and information managers-anyone seeking general knowledge about where the communications industry is heading.

Peripheries of cohesive subsets

Network analysts have developed a number of techniques for identifying cohesive subgroups in networks. In general, however, no consideration is given to actors that do not belong to a given group. In this paper, we explore ways of identifying actors that are not members of a given cohesive subgroup, but who are sufficiently well tied to the group to be considered peripheral members. We then use this information to explore the structure of the network as a whole.

Avoiding Complexity Catastrophe in Coevolutionary Pockets: Strategies for Rugged Landscapes

Can firms and coevolutionary groups suffer from too much interdependent complexity? Is complexity theory an alternative explanation to competitive selection for the emergent order apparent in coevolutionary industry groups? The biologist Stewart Kauffman suggests a theory of complexity catastrophe offering universal principles explaining phenomena normally attributed to Darwinian natural selection theory. Kauffman's complexity theory seems to apply equally well to firms in coevolutionary pockets. Based on complexity theory, four kinds of complexity are identified. Kauffman's “NK[C] model” is positioned “at the edge of chaos” between complexity driven by “Newtonian” simple rules and rule-driven deterministic chaos. Kauffman's insight, which is the basis of the findings in this paper, is that complexity is both a consequence and a cause. Multicoevolutionary complexity in firms is defined by moving natural selection processes inside firms and down to a “parts” level of analysis, in this instance Porter's value chain level, to focus on microstate activities by agents. The assumptions of stochastically idiosyncratic microstates and coevolution in firms are analyzed. Competitive advantage, as a dependent variable, is defined in terms of Nash equilibrium fitness levels. This allows a translation of Kauffman's theory to firms, paying particular attention to (1) how value chain landscapes might be modeled, (2) assumptions underlying Kauffman's models making them amenable to firms, and (3) a delineation of seven of Kauffman's computational experiments. As part of the translation, possible parallels between the application of complexity catastrophe theory to coevolutionary pockets and studies by institutional theorists and social network analysts are discussed. The models derive from spin-glass microstate models resulting in Boolean games. Kauffman's Boolean statistical mechanics is introduced in developing the logic underlying the somewhat simplified NK[C] model. The model allows the use of computational experiments to better understand how the dependent variable—value chain fitness—is affected by changes in the number of internal interdependencies K, the number of coevolutionary links with opponents C, the size of the coevolutionary pocket S, and the number of simultaneous adaptive changes, among other things. Various computational experiments are presented that suggest strategic organizing approaches most likely to foster competitive advantage. High or low Nash equilibrium fitness levels are shown to result from internal and external coevolutionary densities as a function of links among value chain competencies within a firm and between a firm and an opponent. Complexity phenomena appear to suggest a number of expected (and thus validating) and surprising strategies with respect to complex organizational interdependencies. For example, moderate complexity fares best and external coevolutionary complexity sets an upper bound to advantages likely to be gained from internal complexity. Various complexity “lessons” are discussed. Models such as the NK[C] could offer insights into strategic organizing.

Social Networks, Structural Interdependence, and Conjugal Adjustment in Heterosexual, Gay, and Lesbian Couples

This study examines the social networks and conjugal adjustment of heterosexual, gay, and lesbian couples. Partners of 50 heterosexual, 50 gay, and 33 lesbian couples completed a structured interview (n = 266) about their social networks. The three types of couples did not differ in the partners' separate networks. The joint networks of both gay and lesbian couples were bigger, comprised more friends, but had a similar number of kin, relative to heterosexual couples. Hierarchical multiple regression analyses indicated that for heterosexual couples, more balanced inclusion of the two partners' kin in their joint network predicted better conjugal adjustment. For gay couples, less dependency on both separate and shared friends predicted higher conjugal adjustment, and for lesbian couples, fewer separate friends and less dependency on separate kin led to better adjustment. The relevance of social networks to conjugal and family adaptation has been emphasized in research traditions as varied as social ecology (Bronfenbrenner, 1988), network analysis (Milardo, 1986; Key Words: conjugal adjustment, sexual orientation, social network, structural interdependence. Wellman, 1983), and clinical psychology (Coyne & DeLongis, 1986). For instance, social networks have been associated with marital violence (Mitchell & Hodson, 1986), the household division of labor (Bott, 1971), parenting skills (Jenning, Stagg, & Connors, 1991), and marital satisfaction (e.g., Julien, Markman, Leveille, Chartrand, & Begin, 1994; Parks & Eggert, 1991). However, the theories of and the findings on the associations between social networks and relationship outcomes have been based on samples of heterosexual couples and families. We do not know whether they generalize to same-sex couples. Because the homosexual minority in the industrialized West has become increasingly visible and active in recent years (West & Green, 1997), the growing numbers of individuals who have now identified themselves openly as gay or lesbian or bisexual offer opportunities to examine the structures, processes, and outcomes of their relationships, to test the generalizability of current theories of close relationships (Kurdek, 1995a), and to broaden our understanding of the role of social networks in relationship outcomes. We studied the social networks of heterosexual, gay, and lesbian couples. Our objectives were to examine whether the social networks of the three types of couples had different structural features and whether the features of the social network predicted conjugal adjustment. Structurally Created Constraints and Opportunities According to network analysts, social behavior is determined by the pattern of ties among members of a social network, in addition to the independent effects of personal dispositions or dyadic ties (Milardo, 1988). The particular features of a social network influence social behavior because they create constraints and provide opportunities for accessing resources such as information, wealth, power, affection, and support (Wellman, 1983). For instance, a social network composed of members who know and interact with one another is more likely and more able to coordinate support for one of its members in times of stress than a social network in which the members are loosely connected. Network analysis has implications for understanding couples' development. When two individuals choose each other for a committed relationship, they also adopt one another's social network of kin and friends. In doing so, they modify a local social structure that affects their access to resources. Conversely, the theory implies that terminating intimate relationships forces the partners to restructure their social environment in ways that have functional implications for access to resources. Structural Interdependence and Conjugal Outcomes Milardo (1986) has suggested the concept of structural interdependence as a theoretical basis for linking network structure to conjugal outcomes. …

Policy Network Transformation: The Implementation Of The Ec Directive On Packaging And Packaging Waste

Policy network analysis has been criticized for failing to adopt a sufficiently dynamic approach to the study of policy‐making processes. There have been, however, a number of studies illustrating how policy networks change, recognizing that they are not static entities but respond to changes in the policy environment. This article applies policy network analysis to the negotiation of plans to implement the 1994 EC Packaging and Packaging Waste Directive in the UK and provides a further contribution to the literature on the formation and transformation of policy networks. The analysis reveals significant changes in the structure and operation of the policy network during the period studied. The reasons for such changes confirm those put forward by other policy network analysts, such as the power of the actors involved and conflicts between them. Other reasons include the role of the government and the tight schedule laid out by the directive.

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 network analysis: A new methodology for counseling research.

Social network analysis (SNA) is a set of procedures that use indices of relatedness among individuals to produce representations of social structures and positions inherent in dyads or groups. This approach differs from traditional research strategies in that the focus is on developing an understanding of the ongoing transactions and the implications of transactional patterns between individuals, groups, or other social units. Although the primary emphasis in SNA is on the social context, network analysts also include traditional individual-differences variables as potential explanatory factors. SNA methods provide the means to derive a more complete view of a given social environment. A group-psychotherapy example is used to provide an overview of SNA, introducing the concepts, notation, and statistical methods used by the current generation of network researchers. Methodological issues are discussed, applications are reviewed, and resources are recommended for those wishing to learn more about SNA.

Are personal communities local? A Dumptarian reconsideration

Abstract Are local ties important in personal community networks? Since local ties only make up a minority of people's active ties, network analysts have argued for decades that the neighborhood is not very important. Re-analysis of the Toronto data shows that when contacts become the unit of analysis instead of ties, the percentage of local relationships in active networks nearly doubles. Moreover, when we also take into account active contacts with coworkers, who like neighbors are physically proximate, we find that two-thirds of all contacts are ‘local’. As Humpty-Dumpty has cogently reminded us, a network can be anything we want it to be. It depends on how we define it. When we change the definition, the conclusions change too.

The relevance of social network concepts to sexually transmitted disease control.

Many of the concepts of social network analysis have been tacit assumptions of sexually transmitted disease control efforts for decades. With the advent of AIDS in the 1980s, an overt rapprochement between these two fields--previously separated by culture, context, and language--was made. Social network constructs have immediate appeal to disease control workers, who view many diseases as following the conduits of social interactions. STDs and HIV, in turn, provide network analysts and those who model disease transmission with substantial sets of empirical data that test and illuminate theory. Disease control efforts can be enhanced by incorporating network concepts overtly into current practices. Such concepts offer a path to better delineation of groups at risk, to a better understanding of the interaction of personal risk taking and the social context, and to evaluation of control mechanisms.

Partitioning networks based on generalized concepts of equivalence

The idea of partitioning a network in terms of a specific conceptualization of equivalence has taken a powerful hold on the imagination of network analysts. Frequently, an empirically established blockmodel is assessed in terms of its consistency with a particular visualization of a network. We demonstrate that, while a visual representation of a network can be helpful, this also constrains powerfully our image of the structure of that network. This implies that a particular picture of a network is not sufficient for establishing the adequacy of a blockmodel. We argue that once committed to a specific form of equivalence, a network analyst must be committed also to an explicit method of assessing the extent to which a blockmodel is consistent with the selected form of equivalence. We provide a method for doing this. Additionally, and perhaps more importantly, efforts to measure the fit of a blockmodel in terms of a single form of equivalence reveal a serious weakness in the idea of using only a single for...

Cohesion, equivalence, and similarity of behavior: a theoretical and empirical assessment

Abstract Network analysts have debated the extent to which cohesion versus structural equivalence serves as a source of similar behavior among actors. More recently, role equivalence has emerged as an alternative to structural equivalence. Using data on the contribution patterns of corporate political action committees, I examine the effect of various indicators of cohesion, structural equivalence, and role equivalence on the extent to which firms behave similarly. Although various operationalizations of all three concepts are correlated with similar behavior, the most consistent predictor is the joint prominence of two firms in the network. I argue that this common location in central positions is a form of role equivalence, but one that is distinct from conventional definitions of the concept. I then suggest a distinction between what I term ‘central’ and ‘peripheral’ role equivalence.

Network Studies of Social Influence

Network analysts interested in social influence examine the social foundations for influence—the social relations that provide a basis for the alteration of an attitude or behavior by one network actor in response to another. This article contrasts two empirical accounts of social influence (structural cohesion and equivalence) and describes the social processes (e.g., identification, competition, and authority) presumed to undergird them. It then reviews mathematical models of influence processes involving networks and related statistical models used in data analysis. Particular attention is given to the “network effects” model. A number of empirical studies of social influence are reviewed. The article concludes by identifying several problems of specification, research design, and measurement and suggesting some research that would help to resolve these problems.