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Paper

Understanding the Use of Fauxtography on Social Media

MPS-Authors

Wang,  Yuping
Internet Architecture, MPI for Informatics, Max Planck Society;

Tahmasbi,  Fatemeh
Internet Architecture, MPI for Informatics, Max Planck Society;

Blackburn,  Jeremy
Internet Architecture, MPI for Informatics, Max Planck Society;

Bradlyn,  Barry
Internet Architecture, MPI for Informatics, Max Planck Society;

De Cristofaro,  Emiliano
Internet Architecture, MPI for Informatics, Max Planck Society;

Magerman,  David
Internet Architecture, MPI for Informatics, Max Planck Society;

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Zannettou,  Savvas
Internet Architecture, MPI for Informatics, Max Planck Society;

Stringhini,  Gianluca
Internet Architecture, MPI for Informatics, Max Planck Society;

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arXiv:2009.11792.pdf
(Preprint), 4MB

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Citation

Wang, Y., Tahmasbi, F., Blackburn, J., Bradlyn, B., De Cristofaro, E., Magerman, D., et al. (2020). Understanding the Use of Fauxtography on Social Media. Retrieved from https://arxiv.org/abs/2009.11792.


Cite as: https://hdl.handle.net/21.11116/0000-0007-89D9-A
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.