Tuesday, December 10, 2019

Bots Fired: Examining Social Bot Evidence in Online Mass Shooting Conversations

Building upon our work with respect to how bots impact online conversations pertaining to global events and  health,  we have extended this research to see what role bots play in mass shooting events. In our new paper published in Palgrave Communications entitled "Bots Fired: Examining Social Bot Evidence in Online Mass Shooting Conversations" we examine four mass shooting events (i.e., Las Vegas, Sutherland Springs, Parkland, and Santa Fe) and find that social bots participate and contribute to online mass shooting conversations in a manner that is distinguishable from human contributions. Below we provide the abstract, along with some figures from the paper that highlight our methodology and main results. Finally at the bottom of the post, we provide the full reference to the paper. 

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 shooting, 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.

Keywords: Social bots, mass shootings, school shootings, online social networks, computational social science.

 Overview of social bot analysis framework illustrating methodological steps taken to analyze social bots within online social network conversations involving mass shooting events

Overall tweet corpus volumes and suspected social bot contributions for each associated OSN mass shooting 215 event conversation.

Intra-group and cross-group retweet interaction rates among and between human (blue) and suspected social bot (red) user accounts for a one-month period following the (a) Las Vegas, (b) Sutherland Springs, (c) Parkland and (d) Santa Fe shooting events.

Social bot accounts in the top-N, where N = 1000/100/10, (a) eigenvector, (b) in-degree, (c) out-degree and (d) PageRank centrality measurement rankings within OSN mass shooting retweet networks discussing the Las Vegas (red), Sutherland Springs (green), Parkland (blue) and Santa Fe (purple) shooting events.

Full Reference:
Schuchard, R., Crooks, A.T., Croitoru, A. and Stefanidis, A. (2019) Bots Fired: Examining Social Bot Evidence in Online Mass Shooting Conversations, Palgrave Communications, 5: 158. Available at https://doi.org/10.1057/s41599-019-0359-x. (pdf)

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