“I agree with you, bot!” How users (dis)engage with social bots on Twitter

Abstract

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.

Influence of social bots in information warfare: A case study on @UAWeapons Twitter account in the context of Russia–Ukraine conflict

“…In short, the account @UAWeapons utilized hashtags and videos extensively in order to increase its popularity. Furthermore, it was argued that tweets with a clear stance and congruent with the retweeter's perspective are more likely to be disseminated (Wischnewski et al, 2022), which was also confirmed in this study. Despite posting clearly pro-Ukrainian-and anti-Russian content, this account tried to portray itself as a neutral information provider via its profile and hashtag (e.g., the most commonly used hashtag #Ukraine).…”

“…Second, in the case of the information warfare between Russia and Ukraine, it seems doubtful that tweets with a clear stance (Luceri et al, 2019) and that are congruent with the retweeter’s perspective are more likely to be disseminated (Duan et al, 2022; Wischnewski et al, 2022). Politically inclined individuals may be skeptical of neutral news messages that disagree with their views (Hameleers, 2022).…”

Not Our Kind of Crowd! How Partisan Bias Distorts Perceptions of Political Twitter Bots

“…However, contrary to previous findings suggesting that partisans deliberately share any online content that hurts political opponents (Osmundsen et al, 2021), in our study, participants did care whether the profiles they engage with were operated by humans or by bots. Both, Democrats and Republicans favoured engagement with human-driven profiles, hence supporting the idea that human-bot interactions form largely inadvertently (cf., Wischnewski et al, 2022).…”

Editorial: AI and new digital technologies have transformed alcohol and other drug industries lobbying

“…Social bots, for example, are AI-powered applications that automatically produce content and interact with humans (Ferrara et al , 2016). Aside from automating routine commercial tasks such as customer service, bots can be used in corporate PR communication (Wischnewski et al , 2024) and to influence public opinion and attitudes, as illustrated in the political science literature (Godulla et al , 2021). Bots can leave comments, engage in conversations and distribute likes in social media on an automatic and semi-autonomous basis.…”