A taxonomy of bot species on the news aggregation and social media platform Reddit based on temporal, community, linguistic, and semantic features suggests that online bot populations form evolving digital ecosystems.
Abstract
Automated agents increasingly participate in online communities, yet their population structure and roles remain poorly understood. Using a dataset of 3,389 identified bots and their full activity histories, we construct a taxonomy of bot"species"on the news aggregation and social media platform Reddit based on temporal, community, linguistic, and semantic features. Clustering analysis reveals 18 distinct bot types spanning content-specialized, behavior-driven, and infrastructural roles such as moderation and utility support. In addition, temporal analysis shows that bot numbers and activity expanded rapidly before peaking around the COVID-19 period, then started declining even before Reddit's 2023 API policy changes. However, the overall diversity of bot species has remained remarkably stable. These findings suggest that online bot populations form evolving digital ecosystems.
A large-scale empirical analysis of more than 50,000 English-language starter packs and over 600,000 associated users shows that starter packs form a highly interconnected ecosystem with substantial overlap across packs that largely reflects pre-existing communities.
Andrea Failla, V. L. S. Freitas, Giulio Rossetti et al.· 1 citation
In a case study of the reply ecosystem of an official political party account, compute profile-free behavioral features covering text duplication, character-level entropy, timing regularity, reply latency, and post coverage, complemented by a co-commenting network analysis, and group active accounts with unsupervised d...
Kalin Kopanov, Tatiana V. Atanasova· Information· 0 citations
A bibliometric and reflexive thematic analysis of two decades of the most popularly cited research about Wikimedia projects concludes that Wikipedia’s relationship with researchers is a recursive one, since disciplinary choices have changed the cultural meaning and the sociotechnical function of this encyclopedic commu...
As political disruption intensifies online discourse, Bluesky has become an important platform for political discussion and public reaction. In this study, we examine large-scale discourse on Bluesky related to U.S. policy developments associated with the Trump administration. Using the historical retrieval API, we col...
Qile Wang, A. Salloum, Carolina Coimbra Vieira et al.· 0 citations
A 3D visualization approach mapping topics found across a project's socio-technical artifacts onto vegetation-covered islands, where the individual artifacts are depicted as trees of various types.
Adam J. Stepánek, Marco Raglianti, V. Rusňák et al.· 1 citation
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.