A Comparative Analysis of Social Network Topology in Reddit and Moltbook

2026-02-14

AI Summary

This study addresses the empirical gap in comparing the topological structures of AI-driven and human-driven social networks. To this end, it presents the first systematic construction and analysis of a fully AI-agent-based platform, Moltbook (33,577 nodes), alongside the Reddit comment network (7.8 million nodes). Leveraging social network analysis and graph-theoretic metrics, the work rigorously examines differences in network topology and edge formation efficiency between the two systems. The findings reveal distinctive structural characteristics inherent to AI-driven social networks, offering both empirical evidence and theoretical grounding for the development of more realistic and efficient agent-mediated social systems.

Technology Category

• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Humans and AI: Other Foundations of Human Computation & AI
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Social networks and social learning
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

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.

Problem

• social network topology
• agent-driven networks
• human-driven networks
• network comparison
• AI agents

Innovation

• agent-mediated social networks
• network topology
• AI agents
• comparative analysis
• social simulation