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arXiv AI By Shikha Mallick, Alex Thomo, Akrati Saxena

LLMs for Social Network Modeling: From Network Generation to Dynamic Processes

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The paper reviews how large language models (LLMs) are being used to model social networks, highlighting their ability to represent users, relationships, and interactions through natural language. It categorizes existing work into network generative models—split into selection‑based and interaction‑based approaches—and dynamic process models, which cover opinion dynamics, information diffusion, and rumor propagation. The survey also discusses the advantages of LLMs for realistic, context‑aware social behavior, while noting limitations such as social biases and prompt sensitivity, and outlines open research challenges and future directions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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