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On the Role of Semantics for Detecting pro-ISIS Stances on Social Media

Saif, Hassan; Fernández, Miriam; Rowe, Matthew and Alani, Harith (2016). On the Role of Semantics for Detecting pro-ISIS Stances on Social Media. In: Proceedings of the ISWC 2016 Posters & Demonstrations Track co-located with 15th International Semantic Web Conference (ISWC 2016), article no. 66.

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Abstract

From its start, the so-called Islamic State of Iraq and the Levant (ISIL/ISIS) has been successfully exploiting social media networks, most notoriously Twitter, to promote its propaganda and recruit new members, resulting in thousands of social media users adopting pro ISIS stance every year. Automatic identification of pro-ISIS users on social media has, thus, become the centre of interest for various governmental and research organisations. In this paper we propose a semantic-based approach for radicalisation detection on Twitter. Unlike most previous works, which mainly rely on the lexical and contextual representation of the content published by Twitter users, our approach extracts and makes use of the underlying semantics of words exhibited by these users to identify their pro/anti-ISIS stances. Our results show that classifiers trained from words’ semantics outperform those trained from lexical and network features by 2% on average F1-measure.

Item Type: Conference or Workshop Item
Copyright Holders: 2016 The Authors
ISSN: 1613-0073
Keywords: radicalisation detection; semantics; feature engineering; Twitter
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Policing Research and Learning (CPRL)
Centre for Research in Computing (CRC)
Item ID: 48478
Depositing User: Kay Dave
Date Deposited: 20 Feb 2017 16:14
Last Modified: 01 Nov 2017 09:39
URI: http://oro.open.ac.uk/id/eprint/48478
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