Bots increase exposure to negative and inflammatory content in online social systems

By Massimo Stella, Emilio Ferrara, Manlio De Domenico. Proceedings of the National Academy of Sciences of the United States of America, 2018

445 citations recorded by the source corpus.

Significance Social media can deeply influence reality perception, affecting millions of people’s voting behavior. Hence, maneuvering opinion dynamics by disseminating forged content over online ecosystems is an effective pathway for social hacking. We propose a framework for discovering such a potentially dangerous behavior promoted by automatic users, also called “bots,” in online social networks. We provide evidence that social bots target mainly human influencers but generate semantic content depending on the polarized stance of their targets. During the 2017 Catalan referendum, used as a case study, social bots generated and promoted violent content aimed at Independentists, ultimately exacerbating social conflict online. Our results open challenges for detecting and controlling the influence of such content on society. Societies are complex systems, which tend to polarize into subgroups of individuals with dramatically opposite perspectives. This phenomenon is reflected—and often amplified—in online social networks, where, however, humans are no longer the only players and coexist alongside with social bots—that is, software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1, 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, bombarding Independentists with violent contents, increasing their exposure to negative and inflammatory narratives, and exacerbating social conflict online. Our findings stress the importance of developing countermeasures to unmask these forms of automated social manipulation.

Subfields: Artificial Intelligence, Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/ea3c83ebf4572e641514d08f652ad1dea126d91b

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Citations in the corpus

Characterizing the 2016 Russian IRA influence campaign (2018, background): “…González-Bailón et al. (2011), to Occupy Wall Street movements Conover et al. (2013a,b) and other civil protests González-Bailón et al. (2013); Stella et al. (2018); Varol et al. (2014), Twitter and other social media platforms appeared to play an instrumental role in involving the public…”
A decade of social bot detection (2020, background): “In fact, scholars still lack a widespread consensus on the impact of social bots, with some studies reporting on their pivotal role for increasing disinformation’s spread, polarization, and hateful speech [28, 30], and competing results claiming that bots do not play a significant role in these proc”
Arming the public with artificial intelligence to counter social bots (2019, background): “Similar cases of political manipulation were reported in other countries (Stella et al., 2018).”
Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation (2020, background): “…operations and social manipulation [13] have taken place during major events in the past—including in several high profile political instances [14]—and that they might play an important role during other high profile, strategically important or exceptional events, including the COVID-19…”