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Instruments and Tools to Identify Radical Textual Content

Mothe, Josiane; Ullah, Md Zia; Okon, Guenter; Schweer, Thomas; Juršėnas, Alfonsas; Mandravickaitė, Justina

Authors

Josiane Mothe

Guenter Okon

Thomas Schweer

Alfonsas Juršėnas

Justina Mandravickaitė



Abstract

The Internet and social networks are increasingly becoming a media of extremist propaganda. On homepages, in forums or chats, extremists spread their ideologies and world views, which are often contrary to the basic liberal democratic values of the European Union. It is not uncommon that violence is used against those of different faiths, those who think differently, and members of social minorities. This paper presents a set of instruments and tools developed to help investigators to better address hybrid security threats, i.e., threats that combine physical and cyber attacks. These tools have been designed and developed to support security authorities in identifying extremist propaganda on the Internet and classifying it in terms of its degree of danger. This concerns both extremist content on freely accessible Internet pages and content in closed chats. We illustrate the functionalities of the tools through an example related to radicalisation detection; the data used here are just a few tweets, emails propaganda, and darknet posts. This work was supported by the EU granted PREVISION (Prediction and Visual Intelligence for Security Intelligence) project.

Journal Article Type Article
Acceptance Date Mar 18, 2022
Online Publication Date Apr 12, 2022
Publication Date 2022
Deposit Date Mar 13, 2023
Publicly Available Date Mar 15, 2023
Journal Information
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 13
Issue 4
Article Number 193
DOI https://doi.org/10.3390/info13040193
Keywords cybercrime; radical content detection; text analysis; text mining; information extraction; key-phrase extraction; graph-based representation

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