Abstract
Social networks (SNs) are currently the main medium through which terrorist organisations reach out to vulnerable people with the objective of radicalizing and recruiting them to commit violent acts of terrorism. Fortunately, radicalization on social networks has warning signals and indicators that can be detected at the early stages of the radicalization process. In this paper, we explore the use of the semantic web and domain ontologies to automatically mine the radicalisation indicators from messages and posts on social networks.
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References
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Acknowledgment
This work is under the European Regional Development Fund FEDER, and Justice Programme of the European Union (2014–2020) 723180 – RiskTrack –JUST-2015-JCOO-AG/JUST-2015-JCOO-AG-1.
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Barhamgi, M., Lara-Cabrera, R., Benslimane, D., Camacho, D. (2018). Ontology Uses for Radicalisation Detection on Social Networks. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11315. Springer, Cham. https://doi.org/10.1007/978-3-030-03496-2_1
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DOI: https://doi.org/10.1007/978-3-030-03496-2_1
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