Social network dynamics, bots, and community-based online misinformation spread: Lessons from anti-refugee and COVID-19 misinformation cases

Abstract

Networked social influence and strategic information manipulation are two social mechanisms fueling misinformation spread in online communities. However, it is unclear how these two mechanisms differ in their impacts. We conducted social network analyses on two online communities sharing misinformation concerning refugees in 2016 and COVID-19 in 2020. The results robustly showed that online misinformation spread is transitive and positively associated with members’ embedded authority (i.e., the extent to which members’ information is exclusively shared within the focal community). At the same time, strategic misinformation sharing by members of high community loyalty (i.e., targeted information sharing within the community) is less likely to gain momentum. The impact of bots on misinformation is contingent. Findings suggest that networked social influence is a more powerful driver of misinformation spread than strategic information manipulation.

Keywords:

• Bots
• misinformation
• online communities
• social influence
• social networks

Acknowledgement

We would like to thank Janet Fulk, Peter Monge, Emilio Ferrara, Lindsay Young, members of the Annenberg Networks Network, two anonymous reviewers, and the editor for their constructive feedback on the article.

Additional information

Funding

The research is supported by the 2016 Dean’s Big Data/Social Networks Research Grant from Annenberg School for Communication and Journalism, University of Southern California.