Manipulating Twitter through Deletions


  • Christopher Torres-Lugo Indiana University
  • Manita Pote Indiana University
  • Alexander C. Nwala Indiana University
  • Filippo Menczer Indiana University



Social network analysis; communities identification; expertise and authority discovery


Research into influence campaigns on Twitter has mostly relied on identifying malicious activities from tweets obtained via public APIs. By design, these approaches ignore deleted tweets. However, bad actors can delete content strategically to manipulate the system. Here, we provide the first exhaustive, large-scale analysis of anomalous deletion patterns involving more than a billion deletions by over 11 million accounts. Estimates based on publicly available Twitter data underestimate the true deletion volume. A small fraction of accounts delete a large number of tweets daily. We uncover two abusive behaviors that exploit deletions. First, limits on tweet volume are circumvented, allowing certain accounts to flood the network with over 26 thousand daily tweets. Second, coordinated networks of accounts engage in repetitive likes and unlikes of content that is eventually deleted, which can manipulate ranking algorithms. These kinds of abuse can be exploited to amplify content and inflate popularity, while evading detection. Our study provides platforms and researchers with new methods for identifying social media abuse.




How to Cite

Torres-Lugo, C., Pote, M., Nwala, A. C., & Menczer, F. (2022). Manipulating Twitter through Deletions. Proceedings of the International AAAI Conference on Web and Social Media, 16(1), 1029-1039.