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220
The structure and function of complex networks
- SIAM REVIEW
, 2003
"... Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, ..."
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Cited by 2600 (7 self)
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Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Taking stock of networks and organizations. A multilevel perspective
- Acad Manage J
"... The central argument of network research is that actors are embedded in networks of interconnected social relationships that offer opportunities for and constraints on behavior. We review research on the antecedents and consequences of networks at the interpersonal, interunit, and interorganizationa ..."
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Cited by 205 (6 self)
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The central argument of network research is that actors are embedded in networks of interconnected social relationships that offer opportunities for and constraints on behavior. We review research on the antecedents and consequences of networks at the interpersonal, interunit, and interorganizational levels of analysis, evaluate recent theoretical and empirical trends, and give directions for future research, highlighting the importance of investigating cross-level network phenomena. The order of authorship is alphabetical, reflecting equal contributions from the four authors. We thank all reviewers and authors who helped make this special research forum possible, and above all we thank Tom Lee for his strong support throughout this process. A quarter century of social network research in management journals has resulted in the accumulation of many findings in recent years (see, for example, Borgatti and Foster [2003] for a recent
Influentials, Networks, and Public Opinion Formation
- JOURNAL OF CONSUMER RESEARCH
, 2007
"... A central idea in marketing and diffusion research is that influentials—a minority of individuals who influence an exceptional number of their peers—are important to the formation of public opinion. Here we examine this idea, which we call the “influentials hypothesis,” using a series of computer si ..."
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Cited by 143 (0 self)
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A central idea in marketing and diffusion research is that influentials—a minority of individuals who influence an exceptional number of their peers—are important to the formation of public opinion. Here we examine this idea, which we call the “influentials hypothesis,” using a series of computer simulations of interpersonal influence processes. Under most conditions that we consider, we find that large cascades of influence are driven not by influentials, but by a critical mass of easily influenced individuals. Although our results do not exclude the possibility that influentials can be important, they suggest that the influentials hypothesis requires more careful specification and testing than it has received.
Towards identity anonymization on graphs
- In Proceedings of ACM SIGMOD
, 2008
"... The proliferation of network data in various application domains has raised privacy concerns for the individuals involved. Recent studies show that simply removing the identities of the nodes before publishing the graph/social network data does not guarantee privacy. The structure of the graph itsel ..."
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Cited by 123 (6 self)
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The proliferation of network data in various application domains has raised privacy concerns for the individuals involved. Recent studies show that simply removing the identities of the nodes before publishing the graph/social network data does not guarantee privacy. The structure of the graph itself, and in its basic form the degree of the nodes, can be revealing the identities of individuals. To address this issue, we study a specific graph-anonymization problem. We call a graph k-degree anonymous if for every node v, there exist at least k−1 other nodes in the graph with the same degree as v. This definition of anonymity prevents the re-identification of individuals by adversaries with a priori knowledge of the degree of certain nodes. We formally define the graph-anonymization problem that, given a graph G, asks for the k-degree anonymous graph that stems from G with the minimum number of graph-modification operations. We devise simple and efficient algorithms for solving this problem. Our algorithms are based on principles related to the realizability of degree sequences. We apply our methods to a large spectrum of synthetic and real datasets and demonstrate their efficiency and practical utility.
Interorganizational Networks at the Network Level: A review of the empirical literature on whole networks
- Journal of Management
, 2007
"... This article reviews and discusses the empirical literature on interorganizational networks at the network level of analysis, or what is sometimes referred to as “whole ” networks. An overview of the distinction between egocentric and network-level research is first introduced. Then, a review of the ..."
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Cited by 108 (5 self)
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This article reviews and discusses the empirical literature on interorganizational networks at the network level of analysis, or what is sometimes referred to as “whole ” networks. An overview of the distinction between egocentric and network-level research is first introduced. Then, a review of the modest literature on whole networks is undertaken, along with a summary table outlining the main findings based on a thorough literature search. Finally, the authors offer a discussion concerning what future directions might be taken by researchers hoping to expand this important, but understudied, topic. Keywords: interorganizational networks; whole networks; network level of analysis; networks The literature on networks is by now quite extensive. From social networks to organizational networks and beyond, networks have been and continue to be an emerging and developing field of study that has spanned many disciplines, including, but not limited to, organizational theory and behavior, strategic management, business studies, health care †The authors would like to thank Joe Galaskiewicz for his insights and comments during the development of this article.
Neighborhood-Based Models for Social Networks
- Sociological Methodology
, 2002
"... Harrison White and several anonymous reviewers for valuable comments on the work. We argue that social networks can be modeled as the outcome of processes that occur in overlapping local regions of the network, termed local social neighborhoods. Each neighborhood is conceived as a possible site of i ..."
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Cited by 100 (10 self)
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Harrison White and several anonymous reviewers for valuable comments on the work. We argue that social networks can be modeled as the outcome of processes that occur in overlapping local regions of the network, termed local social neighborhoods. Each neighborhood is conceived as a possible site of interaction and corresponds to a subset of possible network ties. In this paper, we discuss hypotheses about the form of these neighborhoods, and we present two new and theoretically plausible ways in which neighborhood-based models for networks can be constructed. In the first, we introduce the notion of a setting structure, a directly hypothesized (or observed) set of exogenous constraints on possible neighborhood forms. In the second, we propose higher-order neighborhoods that are generated, in part, by the outcome of interactive network processes themselves. Applications of both approaches to model construction are presented, and the developments are considered within a general conceptual framework of locale for social networks. We show how assumptions about neighborhoods can be cast within a hierarchy of increasingly complex models; these models represent a progressively greater capacity for network processes to “reach ” across a network through long cycles or semi-paths. We argue that this class of models holds new promise for the development of empirically plausible models for networks and network-based processes. 2 1.
Structure and time evolution of an Internet dating community
, 2004
"... We present statistics for the structure and time evolution of a network constructed from user activity in an Internet community. The vastness and precise time resolution of an Internet community offers unique possibilities to monitor social network formation and dynamics. Time evolution of well-know ..."
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Cited by 61 (7 self)
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We present statistics for the structure and time evolution of a network constructed from user activity in an Internet community. The vastness and precise time resolution of an Internet community offers unique possibilities to monitor social network formation and dynamics. Time evolution of well-known quantities, such as clustering, mixing (degree–degree correlations), average geodesic length, degree, and reciprocity is studied. In contrast to earlier analyses of scientific collaboration networks, mixing by degree between vertices is found to be disassortative. Furthermore, both the evolutionary trajectories of the average geodesic length and of the clustering coefficients are found to have minima.
Mesolevel Networks and the Diffusion of Social Movements: The Case of the Swedish Social Democratic Party.”American
- Journal of Sociology
, 2000
"... In analyzing the spatial diffusion of the Swedish Social Democratic Party, this article introduces the notion of a mesolevel network. A mesolevel network is a social network that differs in three important respects from interpersonal microlevel networks directly linking prior and potential adopters ..."
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Cited by 40 (6 self)
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In analyzing the spatial diffusion of the Swedish Social Democratic Party, this article introduces the notion of a mesolevel network. A mesolevel network is a social network that differs in three important respects from interpersonal microlevel networks directly linking prior and potential adopters of a practice to one another: (1) it is generated by a different causal process than the microlevel network; (2) it tends to be much sparser than the microlevel network; and (3) the typical edge of a mesolevel network bridges much longer sociometric and geographic distances than the typical edge of a microlevel network. These types of mesolevel networks are important because they can dramatically influence the speed at which a contagious practice will diffuse. The mesolevel network focused upon in this article is the network that emerged out of the travel routes of political agitators affiliated with the Social Democratic Party. Computational modeling shows that the diffusion of the Social Democratic Party is likely to have been considerably influenced by the structure of this network. Empirical analyses of the founding of party organizations during the period 1894–1911 support these theoretical predictions and suggest that this mesolevel network was of considerable importance for the diffusion of the Swedish Social Democratic Party.
Small and other worlds: Global network structures from local processes
- American Journal of Sociology
, 2005
"... Using simulation, we contrast global network structures—in particular, small world properties—with the local patterning that generates the network. We show how to simulate Markov graph distributions based on assumptions about simple local social processes. We examine the resulting global structures ..."
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Cited by 39 (2 self)
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Using simulation, we contrast global network structures—in particular, small world properties—with the local patterning that generates the network. We show how to simulate Markov graph distributions based on assumptions about simple local social processes. We examine the resulting global structures against appropriate Bernoulli graph distributions and provide examples of stochastic global “worlds, ” including small worlds, long path worlds, and nonclustered worlds with many four-cycles. In light of these results we suggest a locally specified social process that produces small world properties. In examining movement from structure to randomness, parameter scaling produces a phase transition at a “temperature ” where regular structures “melt ” into stochastically based counterparts. We provide examples of “frozen ” structures, including “caveman ” graphs, bipartite structures, and cyclic structures.
