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Understanding the Use of Fauxtography on Social Media (2009.11792v2)

Published 24 Sep 2020 in cs.CY

Abstract: Despite the influence that image-based communication has on online discourse, the role played by images in disinformation is still not well understood. In this paper, we present the first large-scale study of fauxtography, analyzing the use of manipulated or misleading images in news discussion on online communities. First, we develop a computational pipeline geared to detect fauxtography, and identify over 61k instances of fauxtography discussed on Twitter, 4chan, and Reddit. Then, we study how posting fauxtography affects engagement of posts on social media, finding that posts containing it receive more interactions in the form of re-shares, likes, and comments. Finally, we show that fauxtography images are often turned into memes by Web communities. Our findings show that effective mitigation against disinformation need to take images into account, and highlight a number of challenges in dealing with image-based disinformation.

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Authors (8)
  1. Yuping Wang (56 papers)
  2. Fatemeh Tahmasbi (5 papers)
  3. Jeremy Blackburn (76 papers)
  4. Barry Bradlyn (83 papers)
  5. Emiliano De Cristofaro (117 papers)
  6. David Magerman (1 paper)
  7. Savvas Zannettou (55 papers)
  8. Gianluca Stringhini (77 papers)
Citations (23)