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Terrorism Research

Terrorism Research

Univ.-Prof. Dr. Wolfgang G. Stock

Terrorism research in information science focuses on the content of documents by and about terroristic organizations. Our research includes microblogs on such organizations (as, for instance, ISIS) and reactions on terrorist attacks (such as Charlie Hebdo). We pay particular attention to indexing, informetrical data evaluation, and content analysis of publications of terrorist organizations (such as the Islamic States‘ magazines Dabiq and Rumiyah).



Kling, F., Ilhan, A., Stock, W. G., & Henkel, M. (2018). The Islamic State’s strategic communication: An informetric topic analysis. In Proceedings of the 81st Annual Meeting of the Association for Information Science & Technology | Vancouver, Canada | Nov. 10 - 14, 2018 (pp. 264-273). Silver Spring, MD: Association for Information Science and Technology.

Ruhrberg, S. D., Kirstein, G., Habermann, T., Nikolic, J., & Stock, W. G. (2018). #ISIS - A comparative analysis of country-specific sentiment on Twitter. Open Journal of Social Sciences, 6(6), 142-158.

Ilhan, A., & Fietkiewicz, K. J. (2017). User behavior in the twittersphere: Content analysis of tweets on Charlie Hebdo attacks. In Proceedings of the iConference: Effect, Expand, Evolce. March 22-25, 2017, Wuhan, China (pp. 190-202). University of Illinois at Urbana-Champaign: iSchools, IDEALS.

Fietkiewicz, K. J., & Ilhan, A. (2017). Breaking news commentary: Users' reactions to terrorist attacks in english-speaking Twittersphere. In C. Stephanidis (Ed.), HCI International 2017 - Posters' Extended Abstracts. Part I (pp. 428–434). Cham, Switzerland: Springer (Communications in Computer and Information Science; 713).

Kwiatkowski, M., Höhfeld, S., Kradepohl, I. (2005). Der Einsatz von Ontologien bei Retrieval-Systemen von Intelligence Services - am Beispiel von Convera RetrievalWare. ISC 2005 - Security, Terrorism and Privacy in Information Society. Düsseldorf, 27-28 October 2005. Proceedings of the Third International Security Conference.

Heesemann, S., & Nellißen, H.-D. (2008). Facettierte Wissensordnungen und dynamisches Klassieren als Hilfsmittel der Erforschung des Dark Web. Information — Wissenschaft und Forschung, 59(2), 108-117.

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