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US Domestic Extremist Groups on the Web: Link and Content Analysis
September/October 2005 (vol. 20 no. 5)
pp. 44-51
Yilu Zhou, University of Arizona
Edna Reid, University of Arizona
Jialun Qin, University of Arizona
Hsinchun Chen, University of Arizona
US domestic extremist groups have increased in numbers and are using the Internet intensively as a tool to share resources and members with limited regard for geographic, legal, or other obstacles. Researchers find that monitoring extremist and hate groups? Web sites and analyzing their Web usage and site content have become time consuming and challenging. A semiautomated methodology for capturing, classifying, and organizing domestic extremist Web site data and using it for analysis coincided with expert and manual research results. Analyzing the hyperlink structures and content of domestic extremist Web sites and constructing social network maps identified their interorganizational structure and cluster affinities. Such analysis results could help experts in terrorism, law-reinforcement, intelligence, and policy-making domains better understand the domestic extremist phenomena and eventually boost our national security.

This article is part of a special issue on Homeland Security.

Index Terms:
terrorism, Dark Web, Web harvesting, Web content analysis, Web link analysis, data visualization, Web mining, text mining, decision support systems
Citation:
Yilu Zhou, Edna Reid, Jialun Qin, Hsinchun Chen, Guanpi Lai, "US Domestic Extremist Groups on the Web: Link and Content Analysis," IEEE Intelligent Systems, vol. 20, no. 5, pp. 44-51, Sept.-Oct. 2005, doi:10.1109/MIS.2005.96
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