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Using machine learning to identify jihadist messages on Twitter
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Jihadist groups like 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. However, 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 radical content that is released by jihadist groups on Twitter. We use a machine learning approach that classifies a tweet as radical or non-radical and our results indicate that an automated approach to aid analysts in their work with detecting radical content on social media is a promising way forward.

Place, publisher, year, edition, pages
2015. , 55 p.
Series
IT, 15056
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-260099OAI: oai:DiVA.org:uu-260099DiVA: diva2:846343
Educational program
Master Programme in Computer Science
Supervisors
Examiners
Available from: 2015-08-16 Created: 2015-08-16 Last updated: 2015-08-16Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
  • en-GB
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  • nn-NB
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  • Other locale
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Output format
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