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, Jg. 26 (2024), Heft 3, S. 1505 - 1526
2024Artikel/Aufsatz in ZeitschriftOA Hybrid
PsychologieFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Angewandte Kognitions- und Medienwissenschaft » Sozialpsychologie: Medien und KommunikationFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Informatik » Theoretische Informatik
Damit verbunden: 2 Publikation(en)
Titel in Englisch:
“I agree with you, bot!” : How users (dis)engage with social bots on Twitter
Autor*in:
Wischnewski, MagdalenaUDE
LSF ID
60157
ORCID
0000-0001-6377-0940ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
korrespondierende*r Autor*in
;
Ngo, ThaoUDE
LSF ID
60158
ORCID
0000-0001-5147-8272ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Bernemann, RebeccaUDE
LSF ID
60566
ORCID
0000-0002-3240-0952ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Jansen, Martin-PieterUDE
GND
1319605281
LSF ID
61564
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Krämer, NicoleUDE
GND
123292786
LSF ID
47899
ORCID
0000-0001-7535-870XORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
Erscheinungsjahr:
2024
Open Access?:
OA Hybrid
Web of Science ID
Scopus ID
Sprache des Textes:
Englisch
Schlagwort, Thema:
Human–computer interaction ; motivated reasoning ; social bot ; social influence ; social media ; Twitter
Ressourcentyp:
Text

Abstract in Englisch:

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.