Abstract
RiskTrack is a project supported by the European Union, with the aim of helping security forces, intelligence services and prosecutors to assess the risk of Jihadi radicalization of an individual (or a group of people). To determine the risk of radicalization of an individual, it uses information extracted from its Twitter account. Specifically, the tool uses a combination of linguistic factors to establish a risk value, in order to help the analyst with the decision making. This article aims to describe the linguistic features used on the first prototype of the RiskTrack tool. These factors, along with the way of calculating them and their contribution to the final risk value, will be presented in this paper. Also, some comments about the tool and the next updates will be suggested at the end of this paper.
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Torregrosa, J., Panizo, Á. (2018). RiskTrack: Assessing the Risk of Jihadi Radicalization on Twitter Using Linguistic Factors. 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_3
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DOI: https://doi.org/10.1007/978-3-030-03496-2_3
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