Bots are less central than verified accounts during contentious political events

Sandra González-Bailón () and Manlio De Domenico ()
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Sandra González-Bailón: Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
Manlio De Domenico: Center for Information and Communication Technology, Fondazione Bruno Kessler, 38123 Trento, Italy

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 11, e2013443118

Abstract: Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity.

Keywords: computational social science; online networks; information diffusion; political mobilization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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