Analyzing Toxic Behavior and Its Impact on the Mastodon Community

A new study from researchers at an undisclosed institution uses machine learning to analyze toxic behavior on the decentralized social platform Mastodon, finding that the lack of unified moderation standards across independently operated servers creates unique challenges for detecting and mitigating harmful content. The paper, posted on arXiv on July 24, 2026, examines user posts to clarify toxicity trends and their implications for community health and decentralized governance.

Computer Science Computation and Language Submitted on 24 Jul 2026 Title:Analyzing Toxic Behavior and Its Impact on the Mastodon Community View PDF /pdf/2607.21980 HTML experimental https://arxiv.org/html/2607.21980v1 Abstract:Mastodon as a decentralized federation of independently moderated social servers poses unique challenges for the detection and mitigation of toxic content. There are no unified moderation standards. The ecosystem is very diverse and uneven. This paper explores the development and spread of toxicity in Mastodon, utilizing machine learning methods to examine user posts. The results offer clarity on toxicity trends and its implications for community health and decentralized governance. Submission history From: Pasan Kamburugamuwa view email /show-email/450a71a8/2607.21980 v1 Fri, 24 Jul 2026 04:52:29 UTC 415 KB References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer What is the Explorer? https://info.arxiv.org/labs/showcase.html arxiv-bibliographic-explorer Connected Papers What is Connected Papers? https://www.connectedpapers.com/about Litmaps What is Litmaps? https://www.litmaps.co/ scite Smart Citations What are Smart Citations? https://www.scite.ai/ Code, Data and Media Associated with this Article alphaXiv What is alphaXiv? https://alphaxiv.org/ CatalyzeX Code Finder for Papers What is CatalyzeX? https://www.catalyzex.com DagsHub What is DagsHub? https://dagshub.com/ Gotit.pub What is GotitPub? http://gotit.pub/faq Hugging Face What is Huggingface? https://huggingface.co/huggingface ScienceCast What is ScienceCast? https://sciencecast.org/welcome Demos Recommenders and Search Tools Influence Flower What are Influence Flowers? https://influencemap.cmlab.dev/ CORE Recommender What is CORE? https://core.ac.uk/services/recommender arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs https://info.arxiv.org/labs/index.html .