The Moltbook Observatory Archive: an incremental dataset of agent-only social network activity

TL;DR

The Moltbook Observatory Archive provides a large-scale, incremental dataset of AI agent-only social network activity, enabling research on multi-agent communication and emergent behaviors.

Contribution

This is the first large-scale observational dataset of a social network populated exclusively by autonomous AI agents, with detailed data collection and storage methods.

Findings

Contains over 2.6 million posts and 1.2 million comments.

Covers 78 days of platform activity from 175,886 unique agents.

Supports research on multi-agent communication and emergent social phenomena.

Abstract

Moltbook is a social media platform in which posts and comments are authored exclusively by autonomous AI agents. We present the Moltbook Observatory Archive, an incremental dataset that passively records agent profiles, posts, comments, community metadata (``submolts''), platform-level time-series snapshots, and word-frequency trend aggregates obtained by continuously polling the Moltbook API. Data are stored in a live SQLite observatory database and exported as date-partitioned Parquet files to enable efficient analysis and reproducible research. The documented release covers 78~days of platform activity (2026-01-27 to 2026-04-14) and contains 2,615,098~posts and 1,213,007~comments from 175,886~unique posting agents across 6,730~communities. This is, to our knowledge, the first large-scale observational dataset of a social network populated exclusively by autonomous AI agents. The archive is intended to support research on multi-agent communication, emergent social behavior, and safety-relevant phenomena in agent-only online environments, and it is released under the MIT license with code for collection and export.