Bots into the Fediverse

Bots into the Fediverse | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bots into the Fediverse Francisco Moreno García, Pablo Perdomo Quinteiro, Gustavo Hernandez-Peñaloza, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7600191/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jan, 2026 Read the published version in Social Network Analysis and Mining → Version 1 posted 9 You are reading this latest preprint version Abstract Social bots are a known problem in today’s society. They are influenced by a vari-ety of factors, ranging from the presence of bots to a lack of interaction betweenbots and users. This paper proposes a cross-platform approach for the detectionof social bots based on profile metadata and text embeddings, applied to Twit-ter, Mastodon, and Bluesky user accounts. The resulting model achieves 97.15%accuracy in a four-class classification task, outperforming several establishedbaselines, including graph-based and federated approaches while being compu-tationally efficient. The primary contribution of this work is the demonstrationthat user features can support effective bot classification across heterogeneousand decentralized environments, demonstrating the feasibility of cross-domaingeneralization at scale. We additionally present a novel dataset that combinesself-identified bot and non-bot accounts from decentralized platforms. Bots Fediverse Deep Learning Social Media Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Jan, 2026 Read the published version in Social Network Analysis and Mining → Version 1 posted Editorial decision: Revision requested 07 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviews received at journal 18 Sep, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers invited by journal 14 Sep, 2025 Editor assigned by journal 14 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 12 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7600191","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":515937511,"identity":"7be0a225-5c42-4b20-8c26-3374c3644aa3","order_by":0,"name":"Francisco Moreno 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