Drivers of social influence in the Twitter migration to Mastodon

• Published in: Scientific reports Vol. 13; no. 1; pp. 21626 - 12
• Main Authors: Cava, Lucio La, Aiello, Luca Maria, Tagarelli, Andrea
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 07.12.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/117; 639/705/258; Behavior; Community; Epidemic models; Humanities and Social Sciences; Hypotheses; multidisciplinary; Science; Science (multidisciplinary); Social behavior; Social interaction; Social interactions; Social networks; Social organization
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-48200-7

The migration of Twitter users to Mastodon following Elon Musk’s acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations of the effectiveness of the influence process across different Twitter communities. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in characterizing grassroots collective action, and contribute to deepen our understanding of the mechanisms that drive processes of behavior change of online groups.