Computational Propaganda and Political Big Data: Moving Toward a More Critical Research Agenda

Bolsover, Gillian; Howard, Philip N.

doi:10.1089/big.2017.29024.cpr

Cited by 57 publications

(28 citation statements)

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“…For instance, Serenko, Ruhi, and Cocosila () used a social informatics lens to focus on the ways that intelligent agents on the web had the potential for unintended consequences: reconfiguring work, eroding trust in technology, reducing privacy, and creating social detachment. A decade later, intelligent agents (“bots”) and their ability to create “computational propaganda [have] recently exploded into public consciousness … [and are] both a social and technical phenomenon” (Bolsover & Howard, , p. 273). Social informatics and the willingness to grapple with potential unintended consequences sets this perspective apart from some of the less critical literature on technology innovation.…”

Section: Social Informatics and Knowledgementioning

confidence: 99%

The social informatics of knowledge

Meyer

Shankar

Willis

et al. 2019

Asso for Info Science & Tech

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In the Introduction to this special issue on the Social Informatics of Knowledge, the editors of the issue reflect on the history of the term “social informatics” and how the articles in this issue both reflect and depart from the original concept. We examine how social informatics researchers have studied knowledge, computerization, and the workplace, and how all of those have evolved over time. We describe the process by which articles were included, how they help us understand the field of social informatics scholarship today, and reflect briefly on what the future of the field holds.

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Section: Social Informatics and Knowledgementioning

confidence: 99%

The social informatics of knowledge

Meyer

Shankar

Willis

et al. 2019

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

“…Given the highly contentious policy debates surrounding gun control that are a typical conversational byproduct in the immediate aftermath of a mass shooting event (Merry, 2016;Newman and Hartman, 2017), OSN conversations about mass shootings are a salient topic for digital activists. While a convenient means to access and publish content, OSNs have proven to be complicit in spreading and amplifying manipulated and/or blatantly falsified narratives (Bolsover and Howard, 2017;Lazer et al, 2018;Vosoughi et al, 2018). A primary factor contributing to the skewed narratives in OSNs is the existence of vast populations of social media accounts controlled by social bots (Boshmaf et al, 2013).…”

mentioning

confidence: 99%

Bots fired: examining social bot evidence in online mass shooting conversations

et al. 2019

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Mass shootings, like other extreme events, have long garnered public curiosity and, in turn, significant media coverage. The media framing, or topic focus, of mass shooting events typically evolves over time from details of the actual shooting to discussions of potential policy changes (e.g., gun control, mental health). Such media coverage has been historically provided through traditional media sources such as print, television, and radio, but the advent of online social networks (OSNs) has introduced a new platform for accessing, producing, and distributing information about such extreme events. The ease and convenience of OSN usage for information within society's larger growing reliance upon digital technologies introduces potential unforeseen risks. Social bots, or automated software agents, are one such risk, as they can serve to amplify or distort potential narratives associated with extreme events such as mass shootings. In this paper, we seek to determine the prevalence and relative importance of social bots participating in OSN conversations following mass shooting events using an ensemble of quantitative techniques. Specifically, we examine a corpus of more than 46 million tweets produced by 11.7 million unique Twitter accounts within OSN conversations discussing four major mass shooting events: the 2017 Las Vegas concert shooting, the 2017 Sutherland Springs church chooting, the 2018 Parkland School Shooting and the 2018 Santa Fe school shooting. This study's results show that social bots participate in and contribute to online mass shooting conversations in a manner that is distinguishable from human contributions. Furthermore, while social bots accounted for fewer than 1% of total corpus user contributors, social network analysis centrality measures identified many bots with significant prominence in the conversation networks, densely occupying many of the highest eigenvector and out-degree centrality measure rankings, to include 82% of the top-100 eigenvector values of the Las Vegas retweet network.

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“…The authors argued that this is partially due to the ability of bots to make certain information look popular and to target users with many followers. Similarly, it is widely accepted that computational propaganda from bot accounts on Twitter played a significant role in popularizing Trump's online following, consequently affecting the results of the 2016 presidential election [31,52]. In another study, bots boosted sentiments of alarmism and fear during and after the Catalan referendum in Spain by mimicking the trend of human users' emotional tweets [51].…”

Section: The Influence Of Perceived Prevalence On the Acceptance Of Nmentioning

confidence: 96%

Utilizing Bots for Sustainable News Business: Understanding Users’ Perspectives of News Bots in the Age of Social Media

Hong

2020

Sustainability

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The move of news audiences to social media has presented a major challenge for news organizations. How to adapt and adjust to this social media environment is an important issue for sustainable news business. News bots are one of the key technologies offered in the current media environment and are widely applied in news production, dissemination, and interaction with audiences. While benefits and concerns coexist about the application of bots in news organizations, the current study aimed to examine how social media users perceive news bots, the factors that affect their acceptance of bots in news organizations, and how this is related to their evaluation of social media news in general. An analysis of the US national survey dataset showed that self-efficacy (confidence in identifying content from a bot) was a successful predictor of news bot acceptance, which in turn resulted in a positive evaluation of social media news in general. In addition, an individual’s perceived prevalence of social media news from bots had an indirect effect on acceptance by increasing self-efficacy. The results are discussed with the aim of providing a better understanding of news audiences in the social media environment, and practical implications for the sustainable news business are suggested.

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Computational Propaganda and Political Big Data: Moving Toward a More Critical Research Agenda

Cited by 57 publications

References 0 publications

The social informatics of knowledge

The social informatics of knowledge

Bots fired: examining social bot evidence in online mass shooting conversations

Utilizing Bots for Sustainable News Business: Understanding Users’ Perspectives of News Bots in the Age of Social Media

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