Researchers all over the world in a variety of disciplines are working on developing the means for understanding extremist groups, terrorism and terrorists: their effects on the world; how they communicate, organize and propagate themselves; how they are funded; and who they connect with and why. This project is intended to create a large archive, known as the ?Dark Web Archive,? and a research infrastructure for use by computer and information scientists as well as social scientists studying a wide range of computational problems and social and organizational phenomena. The archive will ultimately comprise testbed data containing thousands of multilingual websites and multimedia files by U.S. domestic, Middle Eastern, and Latin American terrorist and extremist groups.

The intent is to support computer and information science (CIS) researchers in using the Dark Web archive for a wide range of exercises: to develop video and voice recognition technologies, advance information retrieval techniques whether in English or other languages, and improve methodologies in data and text mining as well as machine learning and artificial intelligence. Social scientists will also be able to use the archive, for example, to study dynamic ?dark? networks and the linkages or relationships between organizations, examine use of the web by extremist/terrorist groups, and study the inter-relationship of culture, religion and politics. The Dark Web archive will support the comparison of current and historical data, minimize manual analysis by researchers in the social sciences; and enable the replication of experiments by researchers. In addition to supporting researchers in information, computer and social sciences, this project will also have some utility for the national security sector, including law enforcement and the intelligence community.

The project Web site ( provides access to the Dark Web archive, research infrastructure, and additional information.

National Science Foundation (NSF)
Division of Computer and Network Systems (CNS)
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Maria Zemankova
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University of Arizona
United States
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