Large-Scale Analysis of Political Propaganda on Moltbook

Abstract

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 $κ$= 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.

Figures (4)

• Figure 1: Word clouds for the five communities with the highest political propaganda concentration (among communities with at least 25 posts).
• Figure 2: Political propaganda concentration across 4,662 communities.
• Figure 3: Examples of within- and across-community narrative repetition.
• Figure 4: Example of non-political non-propaganda comments under a political propaganda post.