# Decentralised Moderation for Interoperable Social Networks: A Conversation-based Approach for Pleroma and the Fediverse

arXiv: https://arxiv.org/abs/2404.03048 · HTML: https://mlsanity.com/paper/2404.03048/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 62 references that are in the map.
- First posted on arXiv 3 Apr 2024.

## Builds on (most cited first, 13 of 13)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Deep Learning for Hate Speech Detection in Tweets](https://mlsanity.com/paper/1706.00188/) (2017)
- [Characterizing and Detecting Hateful Users on Twitter](https://mlsanity.com/paper/1803.08977/) (2018)
- [DeepHate: Hate Speech Detection via Multi-Faceted Text Representations](https://mlsanity.com/paper/2103.11799/) (2021)
- [Raiders of the Lost Kek: 3.5 Years of Augmented 4chan Posts from the Politically Incorrect Board](https://mlsanity.com/paper/2001.07487/) (2020)
- [Towards Robust Toxic Content Classification](https://mlsanity.com/paper/1912.06872/) (2019)
- [Toxicity in the Decentralized Web and the Potential for Model Sharing](https://mlsanity.com/paper/2204.12709/) (2022)
- [Design and Evaluation of IPFS: A Storage Layer for the Decentralized Web](https://mlsanity.com/paper/2208.05877/) (2022)
- [Challenges in the Decentralised Web: The Mastodon Case](https://mlsanity.com/paper/1909.05801/) (2019)
- [Flocking to Mastodon: Tracking the Great Twitter Migration](https://mlsanity.com/paper/2302.14294/) (2023)
- [Exploring Content Moderation in the Decentralised Web: The Pleroma Case](https://mlsanity.com/paper/2110.13500/) (2021)
- [Information Consumption and Boundary Spanning in Decentralized Online Social Networks: the case of Mastodon Users](https://mlsanity.com/paper/2203.15752/) (2022)
- [Will Admins Cope? Decentralized Moderation in the Fediverse](https://mlsanity.com/paper/2302.05915/) (2023)

## Built on by (most cited first, 2 of 2)

- [Fedivertex: a Graph Dataset based on Decentralized Social Networks for Trustworthy Machine Learning](https://mlsanity.com/paper/2505.20882/) (2025)
- [Conversation Kernels: A Flexible Mechanism to Learn Relevant Context for Online Conversation Understanding](https://mlsanity.com/paper/2505.20482/) (2025)

## Abstract (arXiv)

The recent development of decentralised and interoperable social networks (such as the "fediverse") creates new challenges for content moderators. This is because millions of posts generated on one server can easily "spread" to another, even if the recipient server has very different moderation policies. An obvious solution would be to leverage moderation tools to automatically tag (and filter) posts that contravene moderation policies, e.g. related to toxic speech. Recent work has exploited the conversational context of a post to improve this automatic tagging, e.g. using the replies to a post to help classify if it contains toxic speech. This has shown particular potential in environments with large training sets that contain complete conversations. This, however, creates challenges in a decentralised context, as a single conversation may be fragmented across multiple servers. Thus, each server only has a partial view of an entire conversation because conversations are often federated across servers in a non-synchronized fashion. To address this, we propose a decentralised conversation-aware content moderation approach suitable for the fediverse. Our approach employs a graph deep learning model (GraphNLI) trained locally on each server. The model exploits local data to train a model that combines post and conversational information captured through random walks to detect toxicity. We evaluate our approach with data from Pleroma, a major decentralised and interoperable micro-blogging network containing 2 million conversations. Our model effectively detects toxicity on larger instances, exclusively trained using their local post information (0.8837 macro-F1). Our approach has considerable scope to improve moderation in decentralised and interoperable social networks such as Pleroma or Mastodon.