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Measuring online affects in a white supremacy forum
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Security)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems. (Security)
Simon Fraser Univ, Sch Criminol, Int CyberCrime Res Ctr, Burnaby, BC, Canada.
2016 (English)In: Proc. 14th International Conference on Intelligence and Security Informatics, IEEE Computer Society, 2016Conference paper (Refereed)
Abstract [en]

Since the inception of the World Wide Web, security agencies, researchers, and analysts have focused much of their attention on the sentiment found on hate-inspired web-forums. Here, one of their goals has been to detect and measure users' affects that are expressed in the forums as well as identify how users' affects change over time. Manual inspection has been one way to do this; however, as the number of discussion posts and sub-forums increase, there has been a growing need for an automated system that can assist humans in their analysis. The aim of this paper, then, is to detect and measure a number of affects expressed in written text on Stormfront. org, the most visited hate forum on the Web. To do this, we used a machine learning approach where we trained a model to recognize affects on three sub-forums: Ideology and Philosophy, For Stormfront Ladies Only, and Stormfront Ireland. The training data consisted of manual annotated data and the affects we focused on were racism, aggression, and worries. Results indicate that even though measuring affects is a subjective process, machine learning is a promising way forward to analyze and measure the presence of different affects on hate forums.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-306904ISI: 000390129600015OAI: oai:DiVA.org:uu-306904DiVA: diva2:1044694
Conference
ISI 2016, September 28–30, Tucson, AZ
Available from: 2016-11-04 Created: 2016-11-04 Last updated: 2017-02-07Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf