Radical Text Detection based on Stylometry

Álvaro de Pablo, Óscar Araque, Carlos Iglesias

Abstract

The Internet has become an effective tool for terrorist and radical groups to spread their propaganda. One of the current problems is to detect these radical messages in order to block them or promote counter-narratives. In this work, we propose the use of stylometric methods for characterizing radical messages. We have used a machine learning approach to classify radical texts based on a corpus of news from radical sources such as the so-called ISIS online magazines Dabiq and Rumiyah, as well as news from general newspapers. The results show that stylometric features are effective for radical text classification.

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Paper Citation


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Radical Text Detection based on Stylometry
SN - 978-989-758-399-5
AU - de Pablo Á.
AU - Araque Ó.
AU - Iglesias C.
PY - 2020
SP - 524
EP - 531
DO - 10.5220/0008971205240531


in Harvard Style

de Pablo Á., Araque Ó. and Iglesias C. (2020). Radical Text Detection based on Stylometry.In Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-399-5, pages 524-531. DOI: 10.5220/0008971205240531


in Bibtex Style

@conference{icissp20,
author={Álvaro de Pablo and Óscar Araque and Carlos Iglesias},
title={Radical Text Detection based on Stylometry},
booktitle={Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2020},
pages={524-531},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008971205240531},
isbn={978-989-758-399-5},
}