Abstract

Jihadist groups such as ISIS are spreading online propaganda using various forms of social media such as Twitter and YouTube. One of the most common approaches to stop these groups is to suspend accounts that spread propaganda when they are discovered. This approach requires that human analysts manually read and analyze an enormous amount of information on social media. In this work we make a first attempt to automatically detect messages released by jihadist groups on Twitter. We use a machine learning approach that classifies a tweet as containing material that is supporting jihadists groups or not. Even tough our results are preliminary and more tests needs to be carried out we believe that results indicate that an automated approach to aid analysts in their work with detecting radical content on social media is a promising way forward. It should be noted that an automatic approach to detect radical content should only be used as a support tool for human analysts in their work.

Keywords:
Social media Computer science Work (physics) Data science Internet privacy World Wide Web Computer security Engineering

Metrics

88
Cited By
21.77
FWCI (Field Weighted Citation Impact)
20
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Terrorism, Counterterrorism, and Political Violence
Social Sciences →  Social Sciences →  Sociology and Political Science
Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
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