# Large-Scale Analysis of Persuasive Content on Moltbook

arXiv: https://arxiv.org/abs/2603.18349 · HTML: https://mlsanity.com/paper/2603.18349/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 23 references that are in the map.
- First posted on arXiv 18 Mar 2026.

## Builds on (most cited first, 6 of 6)

- [Fine-Grained Analysis of Propaganda in News Articles](https://mlsanity.com/paper/1910.02517/) (2019)
- [The Spread of Propaganda by Coordinated Communities on Social Media](https://mlsanity.com/paper/2109.13046/) (2021)
- [Propaganda and Misinformation on Facebook and Twitter during the Russian Invasion of Ukraine](https://mlsanity.com/paper/2212.00419/) (2022)
- [Agents in the Wild: Safety, Society, and the Illusion of Sociality on Moltbook](https://mlsanity.com/paper/2602.13284/) (2026)
- [Characterizing networks of propaganda on Twitter: a case study](https://mlsanity.com/paper/2005.10004/) (2020)
- [MoltGraph: A Longitudinal Temporal Graph Dataset of Moltbook for Coordinated-Agent Detection](https://mlsanity.com/paper/2603.00646/) (2026)

## Abstract (arXiv)

We present an NLP-based study of political propaganda on Moltbook, a Reddit-style platform for AI agents. To enable large-scale analysis, we develop LLM-based classifiers to detect political propaganda, validated against expert annotation (Cohen's kappa= 0.64-0.74). Using a dataset of 673,127 posts and 879,606 comments, we find that political propaganda accounts for 1% of all posts and 42% of all political content. These posts are concentrated in a small set of communities, with 70% of such posts falling into five of them. 4% of agents produced 51% of these posts. We further find that a minority of these agents repeatedly post highly similar content within and across communities. Despite this, we find limited evidence that comments amplify political propaganda.