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Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest

  • ,
  • Christina Neumayer
    ,
  • Jesper Henrichsen
    ,
  • Lucas Beck
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-review

Open access

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-review

Original language

English

Journal (Volume, Issue Number)

Social Science Computer Review

Publication milestones

  • Published - 31/01/2022

Publication status

Published - 31/01/2022

ISSN

0894-4393

Publication IDs

  • Scopus: 85124494913

Abstract

This research quantitatively investigates the impact of violence on the propagation of images in social media in the context of political protest. Using a computational approach, we measure the relative violence of a large set of images shared on Twitter during the protests against the G20 summit in Frankfurt am Main in 2017. This allows us to investigate if more violent content is shared more times and faster than less violent content on Twitter, and if different online communities can be characterized by the level of violence of the visual content they share. The results show that the level of violence in an image tweet does not correlate with the number of retweets and mentions it receives that the time to retweet is marginally lower for image tweets containing a high level of violence and that the level of violence in image tweets differs between communities.

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Captures
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Citations
7