2015/02/24 by Norah Abokhodair, Daisy Yoo, David W. McDonald · 2 citations
Computer Science · Physics and Astronomy · Social Sciences · #Botnet #Computer science #Computer security #Internet privacy #Misinformation and Its Impacts #Opinion Dynamics and Social Influence #Social media #Social network (sociolinguistics) #Spam and Phishing Detection #The Internet #World Wide Web #cs.CL #cs.CY #cs.SI
paper · pdf · doi:10.1145/2675133.2675208
13 pages, 4 figures, Presented at the ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2016)
openalex publication_date 2015/02/24 · arxiv created 2016/04/13 · arxiv updated 2016/04/14 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/29
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.