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Title: Explaining Why Fake Photos are Fake: Does It Work?
Today's disinformation campaigns may use deceptively altered photographs to promote a false narrative. In some cases, viewers may be unaware of the alteration and thus may more readily accept the promoted narrative. In this work, we consider whether this effect can be lessened by explaining to the viewer how an image has been manipulated. To explore this idea, we conduct a two-part study. We started with a survey (n=113) to examine whether users are indeed bad at identifying manipulated images. Our result validated this conjecture as participants performed barely better than random guessing (60% accuracy). Then we explored our main hypothesis in a second survey (n=543). We selected manipulated images circulated on the Internet that pictured political figures and opinion influencers. Participants were divided into three groups to view the original (unaltered) images, the manipulated images, and the manipulated images with explanations, respectively. Each image represents a single case study and is evaluated independently of the others. We find that simply highlighting and explaining the manipulation to users was not always effective. When it was effective, it did help to make users less agreeing with the intended messages behind the manipulation. However, surprisingly, the explanation also had an opposite (e.g.,negative) effect on users' feeling/sentiment toward the subjects in the images. Based on these results, we discuss open-ended questions which could serve as the basis for future research in this area.  more » « less
Award ID(s):
2030521
PAR ID:
10411995
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Proceedings of the ACM on Human-Computer Interaction
Volume:
7
Issue:
GROUP
ISSN:
2573-0142
Page Range / eLocation ID:
1 to 22
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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