Network forms of organization, unlike hierarchies or marketplaces, are agile and are constantly adapting as new links are added and dysfunctional ones dropped. We review some of the theoretical and methodological accomplishments and challenges of contemporary research on organizational networks. We then offer an analytic framework that can be used to specify and statistically test simultaneously multilevel, multitheoretical hypotheses about the structural tendencies of organizational networks. We conclude with an empirical study illustrating some of the capabilities of this framework.
A core axiom of sociology is that social structure affects and is affected by human behavior. The term "social structure" conveys two quite different meanings. One meaning is relational, involving networks of ties between individuals or groups of individuals. A second meaning refers to the contexts containing these individuals. Studies of neighborhood and community effects depend on variability in both types of social structure. Using data from multiple villages in Nang Rong, Thailand, this article documents substantial variability in network structure and shows that network structure covaries with context in meaningful ways, suggesting reciprocal effects of changes in both. Finally, it considers implications of variability in network structure, showing that social cohesion affects the likelihood of finding and interviewing former village residents.A core axiom of sociology is that social structure affects and is affected by human behavior, but exactly what this means is not always clear. The term "social structure" has come to symbolize quite different aspects of the larger world in which people live. One meaning is relational, involving ties between individuals or groupings of individuals such as households. These ties may involve kinship, friendship, neighbor relations, social sup- 1 The research reported in this article was supported by grants R01-HD37896 and R01-HD25482 from the National Institute of Child Health and Human Development. We would like to thank Erika Stone and Rick O'Hara for computer programming, Tom Swasey for graphics, Kammi Schmeer for assistance with literature, and Bridget Riordan for manuscript preparation. Helpful comments on earlier versions of this article were received from
We describe and illustrate methodology for comparing networks from diverse settings. Our empirical base consists of 42 networks from four kinds of species (humans, nonhuman primates, nonprimate mammals, and birds) and covering distinct types of relations such as influence, grooming, and agonistic encounters. The general problem is to determine whether networks are similarly structured despite their surface differences. The methodology we propose is generally applicable to the characterization and comparison of network-level social structures across multiple settings, such as different organizations, communities, or social groups, and to the examination of sources of variability in network structure. We first fit a p * model (Wasserman and Pattison 1996) to each network to obtain estimates for effects of six structural properties on the probability of the graph. We then calculate predicted tie probabilities for each network, using both its own parameter estimates and the estimates from every other network in the collection. Comparison is based on the similarity between sets of predicted tie probabilities. We then use correspondence analysis to represent the similarities among all 42 networks and interpret the resulting configuration using information about the species and relations involved. Results *University of California, Irvine †University of South CarolinaWe acknowledge the helpful comments of the editor and anonymous reviewers. For their encouragement and suggestions on the research, we thank H. Russell Bernard, Linton Freeman, and A. Kimball Romney. We thank Tracy Burkett and Douglas Nigh for making their data available to us. 267show that similarities among the networks are due more to the kind of relation than to the kind of animal.
Infection with the β-herpesvirus human cytomegalovirus (HCMV) is lifelong, causing limited disease in healthy adults, but life threatening in immunocompromised individuals. The viral kinase pUL97, a functional ortholog of cellular cyclin-dependent kinases (CDKs), is critical for HCMV replication and a target for antiviral drug development. Upon kinase inhibition, drug-resistant strains emerge with mutations in UL27, an HCMV gene of unknown function. Using a proteomics approach, we discovered that pUL27 is necessary and sufficient to degrade Tip60, a host acetyltransferase and interacting partner of HIV Tat. Consistent with this, the expression of Tat restored antiviral inhibition of an otherwise resistant HCMV strain. The functional consequence of Tip60 degradation was the induction of the CDK inhibitor p21(Waf1/Cip1) and cell-cycle arrest, representing changes necessary for the antiviral effects of pUL97 inhibition. Consequently, either increasing p21(Waf1/Cip1) expression or decreasing Tip60 levels improved the antiviral activity of the HCMV kinase inhibitor maribavir.
Triadic configurations are fundamental to many social structural processes and provide the basis for a variety of social network theories and methodologies. This paper addresses the question of how much of the patterning of triads is accounted for by lower-order properties pertaining to nodes and dyads. The empirical base is a collection of 82 social networks representing a number of different species (humans, baboons, macaques, bison, cattle, goats, sparrows, caribou, and more) and an assortment of social relations (friendship, negative sentiments, choice of work partners, advice seeking, reported social interactions, victories in agonistic encounters, dominance, and co-observation). Methodology uses low dimensional representations of triad censuses for these social networks, as compared to censuses expected given four lower-order social network properties. Results show that triadic structure is largely accounted for by properties more local than triads: network density, nodal indegree and outdegree distributions, and the dyad census. These findings reinforce the observation that structural configurations that can be realized in empirical social networks are severely constrained by very local network properties, making some configurations extremely improbable.I am grateful to John Boyd, Carter Butts, and Kim Romney for insightful discussions of this research and to members of the UCI social network research group for providing a forum to present these ideas. Two reviewers and the editor of Sociological Methodology provided very helpful comments on an earlier draft. I thank Lin Freeman for sharing data on a number of nonhuman social networks.
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