Bots in online social networks can be used for good or bad but their presence is unavoidable and will increase in the future. To investigate how the interaction networks of bots and humans evolve, we created six social bots on Twitter with AI language models and let them carry out standard user operations. Three different strategies were implemented for the bots: a trend-targeting strategy (TTS), a keywords-targeting strategy (KTS) and a user-targeting strategy (UTS). We examined the interaction patterns such as targeting users, spreading messages, propagating relationships, and engagement. We focused on the emergent local structures or motifs and found that the strategies of the social bots had a significant impact on them. Motifs resulting from interactions with bots following TTS or KTS are simple and show significant overlap, while those resulting from interactions with UTS-governed bots lead to more complex motifs. These findings provide insights into human-bot interaction patterns in online social networks, and can be used to develop more effective bots for beneficial tasks and to combat malicious actors.
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The Impact of Governance Bots on Sense of Virtual Community: Development and Validation of the GOV-BOTs Scale
Bots are increasingly being used for governance-related purposes in online communities, yet no instrumentation exists for measuring how users assess their beneficial or detrimental impacts. In order to support future human-centered and community-based research, we developed a new scale called GOVernance Bots in Online communiTies (GOV-BOTs) across two rounds of surveys on Reddit (N=820). We applied rigorous psychometric criteria to demonstrate the validity of GOV-BOTs, which contains two subscales: bot governance (4 items) and bot tensions (3 items). Whereas humans have historically expected communities to be composed entirely of humans, the social participation of bots as non-human agents now raises fundamental questions about psychological, philosophical, and ethical implications. Addressing psychological impacts, our data show that perceptions of effective bot governance positively contribute to users' sense of virtual community (SOVC), whereas perceived bot tensions may only impact SOVC if users are more aware of bots. Finally, we show that users tend to experience the greatest SOVC across groups of subreddits, rather than individual subreddits, suggesting that future research should carefully re-consider uses and operationalizations of the term community.
more » « less- Award ID(s):
- 1910225
- NSF-PAR ID:
- 10469332
- Publisher / Repository:
- Association of Computing Machinery
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 6
- Issue:
- CSCW2
- ISSN:
- 2573-0142
- Page Range / eLocation ID:
- 1 to 30
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3555563
