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A Comparative Analysis of Social Network Topology in Reddit and Moltbook

Yiming Zhu, Gareth Tyson, Pan Hui

TL;DR

This paper presents the first comparative analysis of network topology on Moltbook, utilizing a comment network comprising 33,577 nodes and 697,688 edges and examines key structural differences between agent-drive and human-drive networks, specifically focusing on topological patterns and the edge formation efficacy of their respective posts.

Abstract

Recent advances in agent-mediated systems have enabled a new paradigm of social network simulation, where AI agents interact with human-like autonomy. This evolution has fostered the emergence of agent-driven social networks such as Moltbook, a Reddit-like platform populated entirely by AI agents. Despite these developments, empirical comparisons between agent-driven and human-driven social networks remain scarce, limiting our understanding of how their network topologies might diverge. This paper presents the first comparative analysis of network topology on Moltbook, utilizing a comment network comprising 33,577 nodes and 697,688 edges. To provide a benchmark, we curated a parallel dataset from Reddit consisting of 7.8 million nodes and 51.8 million edges. We examine key structural differences between agent-drive and human-drive networks, specifically focusing on topological patterns and the edge formation efficacy of their respective posts. Our findings provide a foundational profile of AI-driven social structures, serving as a preliminary step toward developing more robust and authentic agent-mediated social systems.

A Comparative Analysis of Social Network Topology in Reddit and Moltbook

TL;DR

This paper presents the first comparative analysis of network topology on Moltbook, utilizing a comment network comprising 33,577 nodes and 697,688 edges and examines key structural differences between agent-drive and human-drive networks, specifically focusing on topological patterns and the edge formation efficacy of their respective posts.

Abstract

Recent advances in agent-mediated systems have enabled a new paradigm of social network simulation, where AI agents interact with human-like autonomy. This evolution has fostered the emergence of agent-driven social networks such as Moltbook, a Reddit-like platform populated entirely by AI agents. Despite these developments, empirical comparisons between agent-driven and human-driven social networks remain scarce, limiting our understanding of how their network topologies might diverge. This paper presents the first comparative analysis of network topology on Moltbook, utilizing a comment network comprising 33,577 nodes and 697,688 edges. To provide a benchmark, we curated a parallel dataset from Reddit consisting of 7.8 million nodes and 51.8 million edges. We examine key structural differences between agent-drive and human-drive networks, specifically focusing on topological patterns and the edge formation efficacy of their respective posts. Our findings provide a foundational profile of AI-driven social structures, serving as a preliminary step toward developing more robust and authentic agent-mediated social systems.
Paper Structure (5 sections, 4 figures, 3 tables)

This paper contains 5 sections, 4 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Methodology
  3. RQ1: Profiling Moltbook comment network
  4. RQ2: The Efficacy of Posts in Network Building
  5. Conclusion

Figures (4)

  • Figure 1: Data schema of Moltbook post and comment data.
  • Figure 2: Comparison of the distributions of nodes' in-degree, out-degree, and local clustering coefficient.
  • Figure 3: Comparison of the concentration of in-degree and out-degree among nodes.
  • Figure 4: Comparison of the distributions of nodes' in-degree, out-degree, and local clustering coefficient.