  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.
