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Social Network Analysis and Mining

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01.12.2021 | Original Article

Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey

verfasst von: Candice Lanius, Ryan Weber, William I. MacKenzie Jr.

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2021

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Abstract

The COVID-19 infodemic is driven partially by Twitter bots. Flagging bot accounts and the misinformation they share could provide one strategy for preventing the spread of false information online. This article reports on an experiment (N = 299) conducted with participants in the USA to see whether flagging tweets as coming from bot accounts and as containing misinformation can lower participants’ self-reported engagement and attitudes about the tweets. This experiment also showed participants tweets that aligned with their previously held beliefs to determine how flags affect their overall opinions. Results showed that flagging tweets lowered participants’ attitudes about them, though this effect was less pronounced in participants who frequently used social media or consumed more news, especially from Facebook or Fox News. Some participants also changed their opinions after seeing the flagged tweets. The results suggest that social media companies can flag suspicious or inaccurate content as a way to fight misinformation. Flagging could be built into future automated fact-checking systems and other misinformation abatement strategies of the social network analysis and mining community.

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Titel: Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey
verfasst von: Candice Lanius
Ryan Weber
William I. MacKenzie Jr.
Publikationsdatum: 01.12.2021
Verlag: Springer Vienna
Erschienen in: Social Network Analysis and Mining / Ausgabe 1/2021
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI: https://doi.org/10.1007/s13278-021-00739-x

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