Abstract
Images are powerful. Visual information can attract attention, improve persuasion, trigger stronger emotions, and is easy to share and spread. We examine the characteristics of the popular images shared on Twitter as part of "Stop the Steal'', the widespread misinformation campaign during the 2020 U.S. election. We analyze the spread of the forty most popular images shared on Twitter as part of this campaign. Using a coding process, we categorize and label the images according to their type, content, origin, and role, and perform a mixed-method analysis of these images' spread on Twitter. Our results show that popular images include both photographs and text rendered as image. Only very few of these popular images included alleged photographic evidence of fraud; and none of the popular photographs had been manipulated. Most images reached a significant portion of their total spread within several hours from their first appearance, and both popular- and less-popular accounts were involved in various stages of their spread.
| Original language | American English |
|---|---|
| Article number | 541 |
| Journal | Proceedings of the ACM on Human-Computer Interaction |
| Volume | 6 |
| Issue number | 2 CSCW |
| DOIs | |
| State | Published - 11 Nov 2022 |
Keywords
- 2020 u.s. election
- Social media
- Visual communication
- Visual misinformation
All Science Journal Classification (ASJC) codes
- Social Sciences (miscellaneous)
- Human-Computer Interaction
- Computer Networks and Communications