Volume 33, Issue 1, 2013

Issue 1, 1-59
“It Takes a Network”: The Rise and Fall of Social Network Analysis in U.S. Army Counterinsurgency Doctrine, 1-10
David Knoke
During the Iraq and Afghanistan Wars, a group of warrior-thinkers developed a new U.S. Army counterinsurgency (COIN) doctrine to fight modern “jihadist” insurgencies. Drawing heavily on social network analysis ideas, COIN principles emphasized population protection and organizational learning and adaptation. As implemented in Iraq by General David Petraeus, the doctrine greatly reduced intercommunal violence although other factors also contributed. But, COIN in Afghanistan under General Stanley McChrystal was unsuccessful in ending the Taliban insurgency. Although the Obama Administration substantially diminished the U.S. Army’s counterinsurgency capabilities, social network analytic ideas persist in military policy and practices.
A Computationally Efficient Approximation of Beta Centrality, 11-17
Zachary Neal
Much attention has been focused on developing methods of assessing centrality and power in networks, with particular interest focused on recursive measures that view the status of a node as a function of the status of other nodes. Although such measures have been widely adopted in both academic research and commercial applications, they are computationally intensive and subject to misspecification. This paper introduces a simple measure, alter-based centrality, as a computationally efficient approximation of one commonly used recursive measure, beta centrality. Comparison of these measures in simulated networks indicates that alter-based centrality offers a robust approximation of beta centrality in non-bipartite networks that is computationally efficient and not subject to misspecification.
Community Structure in Multi-Mode Networks: Applying an Eigenspectrum Approach, 18-23
David Melamed, Ronald L. Breiger & A. Joseph West
We combine the logic of multi-mode networks developed in Fararo and Doreian (1984) with Newman’s (2006) spectral partitioning of graphs into communities. The resulting generalization of spectral partitioning provides a simple, elegant, and useful tool for discovering the community structure of multi-mode graphs. We apply the generalized procedure to a published three-mode network and find that the results of the algorithm are consistent with existing substantive knowledge. We also report the results of extensive simulations, which reveal that the generalization be- comes more effective as the networks become denser.
Injection Drug Users’ Involvement In Drug Economy: Dynamics of Sociometric and Egocentric Social Networks, 24-34
Cui Yang, Carl Latkin, Stephen Q. Muth & Abby Rudolph
The purpose of this analysis was to examine the effect of social network cohesiveness on drug economy involvement, and to test whether this relationship is mediated by drug support network size among a sample of. Involvement in the drug economy was defined by self-report of participation in at least one of the following activities: selling drugs, holding drugs or money for drugs, providing street security for drug sellers, cutting/packaging/cooking drugs, selling or renting drug paraphernalia (e.g., pipes, tools, rigs), and injecting drugs in others’ veins. The sample consists of 273 active injection drug users in Baltimore, Maryland who reported having injected drugs in the last 6 months and were recruited through either street outreach or by their network members. Egocentric drug support networks were assessed through a social network inventory at baseline. Sociometric networks were built upon the linkages by selected matching characteristics, and k-plex rank was used to characterize the level of cohesiveness of the individual to others in the social network. Although no direct effect was observed, structural equation modeling indicated k-plex rank was indirectly associated with drug economy involvement through drug support network size. These findings suggest the effects of large-scale sociometric networks on injectors’ drug economy involvement may occur through their immediate egocentric networks. Future harm reduction programs for injection drug users (IDUs) should consider providing programs coupled with economic opportunities to those drug users within a cohesive network subgroup. Moreover, individuals with a high connectivity to others in their network may be optimal individuals to train for diffusing HIV prevention messages.

Brief Reports

Social Conformity in Networks, 35-42
Ian McCulloh
Centrality in a social network is found to have a significant effect on Asch-type conformity. Friendship affinity andrespect social network data was collected on two different groups of actors. The effects of Asch-type conformitywere empirically tested on central actors and peripheral actors in each group using a culturally appropriate version ofAsch’s test. Findings show that central actors are less willing to conform and peripheral actors are more willing toconform than expected in Asch-type social conformity experiments.

Data Exchange Network

The “AIRNET2000” Data and AIRNET Program, 43-45
Zachary Neal
Multi-Relational International Trade Networks, 1965-2000, 46-49
Matthew C. Mahutga

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INSNA is the professional association for researchers interested in social network analysis. The association is a non-profit organization incorporated in the state of Delaware and founded in 1977.



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