2019/05/29 by Guido Caldarelli, Rocco De Nicola, Fabio Del Vigna +2 · 1 voice · 2 citations
Computer Science · Physics and Astronomy · Social Sciences · #Misinformation and Its Impacts #Opinion Dynamics and Social Influence #Spam and Phishing Detection #cs.SI
paper · pdf · doi:10.1038/s42005-020-0340-4
openalex created_date 2019/06/07 · openalex publication_date 2020/05/11 · openalex updated_date 2026/07/28
Abstract Nowadays, Social Media are a privileged channel for news spreading, information exchange, and fact checking. Unexpectedly for many users, automated accounts, known as social bots, contribute more and more to this process of information diffusion. Using Twitter as a benchmark, we consider the traffic exchanged, over one month of observation, on the migration flux from Northern Africa to Italy. We measure the significant traffic of tweets only, by implementing an entropy-based null model that discounts the activity of users and the virality of tweets. Results show that social bots play a central role in the exchange of significant content. Indeed, not only the strongest hubs have a number of bots among their followers higher than expected, but furthermore a group of them, that can be assigned to the same political tendency, share a common set of bots as followers. The retweeting activity of such automated accounts amplifies the hubs’ messages.