Abstract
AbstractNowadays, 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.
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy
Reference75 articles.
1. Kwak, H., Lee, C., Park, H. & Moon, S. What is Twitter, a social network or a news media? In Proc. 19th International Conference on World Wide Web, WWW ’10, 591–600 (ACM, New York, 2010).
2. Hu, M. et al. Breaking news on Twitter. In Proc. SIGCHI Conference on Human Factors in Computing Systems, CHI ’12, 2751–2754 (ACM, New York, 2012).
3. Gangware, C. & Nemr, W. Weapons of Mass Distraction: Foreign State-Sponsored Disinformation in the Digital Age (Park Advisors, 2019).
4. Bovet, A. & Makse, H. A. Influence of fake news in Twitter during the 2016 US presidential election. Nat. Commun. 10, 7 (2019).
5. Bastos, M. T. & Mercea, D. TheBrexit botnet and user-generated hyperpartisan news. Soc. Sci. Comput. Rev. 37, 38–54 (2017).
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