Dissecting a Social Botnet: Growth, Content and Influence in Twitter

By Norah Abokhodair, Daisy Yoo, David W. Mcdonald. 2015

269 citations recorded by the source corpus.

Social botnets have become an important phenomenon on social media. There are many ways in which social bots can disrupt or influence online discourse, such as, spam hashtags, scam twitter users, and astroturfing. In this paper we considered one specific social botnet in Twitter to understand how it grows over time, how the content of tweets by the social botnet differ from regular users in the same dataset, and lastly, how the social botnet may have influenced the relevant discussions. Our analysis is based on a qualitative coding for approximately 3000 tweets in Arabic and English from the Syrian social bot that was active for 35 weeks on Twitter before it was shutdown. We find that the growth, behavior and content of this particular botnet did not specifically align with common conceptions of botnets. Further we identify interesting aspects of the botnet that distinguish it from regular users.

Subfields: Information Systems, Sociology and Political Science, Statistical and Nonlinear Physics

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Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Bots and spamming accounts are increasingly prevalent (Abokhodair et al., 2015; Ferrara et al., 2016).”
The rise of social bots (2014, background): “Analysis by manual annotators of interactions and content produced by a Syrian social botnet active in Twitter for 35 weeks suggests that some advanced social bots may no longer aim at mimicking human behavior, but rather at misdirecting attention to irrelevant information.(1) Such smoke screening s”
Deep Neural Networks for Bot Detection (2018, background): “…Sometimes, large groups of bots are controlled by the same entity, called bot master , acting behind the scenes in a command-and-control fashion, in analogy to traditional botnets used to deploy cyber attacks and other cyber-security threats [25], as demonstrated on Twitter as well [1, 16].”
Arming the public with artificial intelligence to counter social bots (2019, background): “Abokhodair et al. (2015) dissected a botnet that tried to misdirect the online discussion during the Syrian civil war in 2012.”