{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T06:02:13Z","timestamp":1778565733262,"version":"3.51.4"},"reference-count":49,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T00:00:00Z","timestamp":1644278400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["New Media &amp; Society"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:p>This article investigates under which conditions users on Twitter engage with or react to social bots. Based on insights from human\u2013computer 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\u2019s partisanship. In a preregistered 3 \u00d7 2 within-subject experiment, we asked N\u2009=\u2009223 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.<\/jats:p>","DOI":"10.1177\/14614448211072307","type":"journal-article","created":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T07:52:16Z","timestamp":1644306736000},"page":"1505-1526","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":30,"title":["\u201cI agree with you, bot!\u201d How users (dis)engage with social bots on Twitter"],"prefix":"10.1177","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6377-0940","authenticated-orcid":false,"given":"Magdalena","family":"Wischnewski","sequence":"first","affiliation":[{"name":"University of Duisburg-Essen, Germany"}]},{"given":"Thao","family":"Ngo","sequence":"additional","affiliation":[{"name":"University of Duisburg-Essen, Germany"}]},{"given":"Rebecca","family":"Bernemann","sequence":"additional","affiliation":[{"name":"University of Duisburg-Essen, Germany"}]},{"given":"Martin","family":"Jansen","sequence":"additional","affiliation":[{"name":"University of Duisburg-Essen, Germany"}]},{"given":"Nicole","family":"Kr\u00e4mer","sequence":"additional","affiliation":[{"name":"University of Duisburg-Essen, Germany"}]}],"member":"179","published-online":{"date-parts":[[2022,2,8]]},"reference":[{"issue":"3","key":"bibr1-14614448211072307","first-page":"1","volume":"6","author":"Assenmacher D","year":"2020","journal-title":"Social Media and Society"},{"key":"bibr2-14614448211072307","doi-asserted-by":"publisher","DOI":"10.1080\/01972243.2015.1020197"},{"key":"bibr3-14614448211072307","doi-asserted-by":"publisher","DOI":"10.1177\/0956797615594620"},{"key":"bibr4-14614448211072307","doi-asserted-by":"publisher","DOI":"10.5210\/fm.v21i11.7090"},{"key":"bibr5-14614448211072307","doi-asserted-by":"publisher","DOI":"10.1007\/s11109-013-9238-0"},{"key":"bibr6-14614448211072307","volume-title":"Are Filter Bubbles Real?","author":"Bruns A","year":"2019"},{"key":"bibr7-14614448211072307","unstructured":"Cardoso F, Luceri L, Giordano S (2019) Digital weapons in social media manipulation campaigns 2018\u20132020. http:\/\/workshop-proceedings.icwsm.org\/pdf\/2020_32.pdf"},{"key":"bibr8-14614448211072307","doi-asserted-by":"publisher","DOI":"10.1080\/08941920.2018.1463422"},{"key":"bibr9-14614448211072307","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2020.124163"},{"key":"bibr10-14614448211072307","unstructured":"Cinelli M, De Francisci Morales G, Galeazzi A, et al. 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