Eric W. Schoon

Comparative configurational analysis as a two-mode network problem: A study of terrorist group engagement in the drug trade

Abstract We generalize a form of two-mode network analysis to make it applicable to a cases-by-variables data format, and apply our approach for the study of terrorist group engagement in the drug trade, emphasizing the implications of our approach for policy in a study of 395 terrorist organizations. Based on the organizations’ levels of resources, network connectivity to other groups, ideological emphasis, and participation in multiple illicit economies, we identify several distinctive configurations of factors that lead to multiple types of drug activity. We also demonstrate a technique for assessing sampling variability in configurational models.

The Duality of Clusters and Statistical Interactions

We contend that clusters of cases co-constitute statistical interactions among variables. Interactions among variables imply clusters of cases within which statistical effects differ. Regression coefficients may be productively viewed as sums across clusters of cases, and in this sense regression coefficients may be said to be “composed” of clusters of cases. We explicate a four-step procedure that discovers interaction effects based on clusters of cases in the data matrix, hence aiding in inductive model specification. We illustrate with two examples. One is a reanalysis of data from a published study of the effect of social welfare policy extensiveness on poverty rates across 15 countries. The second uses General Social Survey data to predict four different dimensions of ego-network homophily. We find support for our contention that clusters of the rows of a data matrix may be exploited to discover statistical interactions among variables that improve model fit.

Facebook’s Boundaries:

Facebook was established to help students keep in touch after graduation, but now it’s being credited with major roles in everything from domestic elections to international uprisings. In its no-longer-insular world, Facebook transforms the private into the public.

Using organizational similarity to identify statistical interactions for improving situational awareness of CBRN activities

Distinctive combinations of attributes and behaviors lead us to improve on existing representations of terrorist organizations within a space of group properties. We review and extend a four-step procedure that discovers (statistical) interaction effects among relevant variables based on clusters of organizations derived from group properties. Application of this procedure to 395 terrorist groups in the period 1998-2005 identifies distinctive patterns of unconventional weapons activity and improves prediction of the groups that use or pursue chemical, biological, radiological, or nuclear (CBRN) weapons.

Building Legitimacy: Interactional Dynamics and the Popular Evaluation of the Kurdistan Workers’ Party (PKK) in Turkey

Abstract Previous research has identified a variety of general mechanisms to explain how insurgents build legitimacy. Yet, there is often a gap between these mechanisms and the interactional dynamics of insurgencies. This article attempts to bridge this gap through a theoretically informed analysis of the Kurdistan Workers’ Party’s (PKK) insurgency in Turkey. I show how the PKK’s efforts to cultivate legitimacy, Turkey’s counterinsurgency strategies, and civilian perceptions of the PKK, all mutually influenced one another. Based on this analysis, I argue that the mechanisms that produce popular legitimacy coevolve with insurgents’ behaviors, states’ interventions, and civilians’ perceptions.