Disrupting Dark Networks focuses on how social network analysis can be used to craft strategies to track, destabilize and disrupt covert and illegal networks. The book begins with an overview of the key terms and assumptions of social network analysis and various counterinsurgency strategies. The next several chapters introduce readers to algorithms and metrics commonly used by social network analysts. They provide worked examples from four different social network analysis software packages (UCINET, NetDraw, Pajek and ORA) using standard network data sets as well as data from an actual terrorist network that serves as a running example throughout the book. The book concludes by considering the ethics of and various ways that social network analysis can inform counterinsurgency strategizing. By contextualizing these methods in a larger counterinsurgency framework, this book offers scholars and analysts an array of approaches for disrupting dark networks.
Congregational attendance data are abundant, accessible, and relevant for religious research. Weekly attendance histories provide information about worshippers, congregations, and denominations that surveys cannot capture. The histories yield novel measures of commitment, testable implications of rational choice theory, and compelling evidence that attendance responds strongly to changes in the opportunity cost of time.In a world where "there is no new thing under the sun" the deck most certainly is stacked against original research. And all the more so for a subject like church attendance wherein scholars have wearied their flesh in the making of many books for more than 40 years (Ecclesiastes 1:9, 11:12). Researchers have sliced and diced their data in every conceivable manner. With hundreds of surveys and scores of statistics, they have produced thousands of findings on the causes, consequences, and characteristics of church attendance, to say nothing of its long-run trends, demographic correlates, and cross-national variation.Yet the empirical edifice stands on a dangerously narrow base-a small set of survey questions, including Gallup's "Did you yourself happen to attend church within the past seven days?" and the GSS-style "How often do you attend religious services?" The hazards of inferring so much from so little are illustrated by the hotly debated claims of Hadaway, Marler, and Chaves (1993) that national polls overstate actual rates by a whopping 100 percent. 1 Religious research would benefit from more attention to other sources of information. 2 In particular, it would benefit from more and better use of the attendance counts taken each week at thousands of congregations all over America and, indeed, all over the world. Although a poor substitute for standard survey statistics, these numbers have their own special strengths, and their applications range from cataloging facts to testing theory.For any given congregation, attendance counts tell us much about the health of the church, the habits of its members, and the interplay of religious "supply" and "demand." By comparing the attendance series of congregations from different denominations, we see aspects of denominational culture that surveys cannot capture. As with standard studies of attendance, weekly counts yield even more information when analyzed together with related data, including contributions, congregational characteristics, and the local environment.This article explores some salient features of weekly attendance data. We keep the analysis simple, lest statistical subtleties obscure the message that these data are abundant, informative, easily obtained, and immediately relevant both to theory and applied research. We also frame our findings in terms of rational choice, in part because attendance patterns so clearly follow shifts in cost and benefit, but mostly because it underscores the data's relevance for contemporary scholarship.Personal choice is, of course, the fundamental feature of modern religious observance-be it Christian, J...
The causes of religious violence have attracted numerous explanations in the years since the 9/11 attacks on the Pentagon and the World Trade Towers. However, most forms of religious extremism do not result in violence (e.g., the Amish, Hasidim, Jains) and religious groups have not cornered the market on egregious violence. Nevertheless, religious violence does occur, and this paper examines the interplay of social networks and religious violence. It builds on Cass Sunstein's “law of group polarization,” which predicts that when like-minded people deliberate as an organized group, the general opinion shifts toward extreme versions of their common belief. It argues that internally dense religious groups that maintain few ties to the wider society are more likely to embrace extreme views and behavior than are those that are not as dense and/or remain tied to the wider society. The argument is then tested using social network analysis methodologies to examine the evolution of the Hamburg Cell, which played a critical role in the 9/11 terrorist attacks. It concludes with a series of policy recommendations that can limit but not eliminate religious extremism and violent behavior in the future.
To date, most social network analyses (SNAs) of terrorist groups have used network data that provide snap-shots of the groups at a single point in time. Seldom have they used network data that take into account how the groups have changed over time. In this article, a unique longitudinal network data set, the Noordin Top terrorist network from 2001 to 2010, is examined in order to explore whether a recently developed method -social network change detection (SNCD) -can help analysts monitor a dark network's topography (e.g. centralization, density, degree of fragmentation) in order to detect significant changes in its structure and identify possible causes. The application of change detection to this historical data set illustrates the method's potential usefulness, including its ability to detect significant changes in the network in response to a series of exogenous factors, such as the acquisition of bombing materials, the capture of key leaders and groups, and the death of Noordin himself. The method's inability to detect other significant events, however, highlights important limitations when working with it. While SNCD should not be the only method analysts have at their disposal, the results detailed in this article suggest that it should be included in their toolkit.
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