Wischnewski, Magdalena; Ngo, Thao; Bernemann, Rebecca; Jansen, Martin-Pieter; Krämer, Nicole:
“I agree with you, bot!” : How users (dis)engage with social bots on Twitter
In: New Media and Society, Vol. 26 (2024), No. 3, pp. 1505 - 1526
2024article/chapter in journalOA Hybrid
PsychologyFaculty of Engineering » Computer Science and Applied Cognitive Science » Angewandte Kognitions- und Medienwissenschaft » Social Psychology - Media and CommunicationFaculty of Engineering » Computer Science and Applied Cognitive Science » Computer Science » Theoretical Computer Science
Related: 2 publication(s)
Title in English:
“I agree with you, bot!” : How users (dis)engage with social bots on Twitter
Author:
Wischnewski, MagdalenaUDE
LSF ID
60157
ORCID
0000-0001-6377-0940ORCID iD
Other
connected with university
corresponding author
;
Ngo, ThaoUDE
LSF ID
60158
ORCID
0000-0001-5147-8272ORCID iD
Other
connected with university
;
Bernemann, RebeccaUDE
LSF ID
60566
ORCID
0000-0002-3240-0952ORCID iD
Other
connected with university
;
Jansen, Martin-PieterUDE
GND
1319605281
LSF ID
61564
Other
connected with university
;
Krämer, NicoleUDE
GND
123292786
LSF ID
47899
ORCID
0000-0001-7535-870XORCID iD
Other
connected with university
Year of publication:
2024
Open Access?:
OA Hybrid
Web of Science ID
Scopus ID
Language of text:
English
Keyword, Topic:
Human–computer interaction ; motivated reasoning ; social bot ; social influence ; social media ; Twitter
Type of resource:
Text

Abstract in English:

This article investigates under which conditions users on Twitter engage with or react to social bots. Based on insights from human–computer interaction and motivated reasoning, we hypothesize that (1) users are more likely to engage with human-like social bot accounts and (2) users are more likely to engage with social bots which promote content congruent to the user’s partisanship. In a preregistered 3 × 2 within-subject experiment, we asked N = 223 US Americans to indicate whether they would engage with or react to different Twitter accounts. Accounts systematically varied in their displayed humanness (low humanness, medium humanness, and high humanness) and partisanship (congruent and incongruent). In line with our hypotheses, we found that the more human-like accounts are, the greater is the likelihood that users would engage with or react to them. However, this was only true for accounts that shared the same partisanship as the user.