Are LLM-Powered Social Media Bots Realistic?

Fuente: arXiv
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Autores principales: Ng, Lynnette Hui Xian, Carley, Kathleen M.
Formato: Preprint
Publicado: 2025
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author Ng, Lynnette Hui Xian
Carley, Kathleen M.
author_facet Ng, Lynnette Hui Xian
Carley, Kathleen M.
contents As Large Language Models (LLMs) become more sophisticated, there is a possibility to harness LLMs to power social media bots. This work investigates the realism of generating LLM-Powered social media bot networks. Through a combination of manual effort, network science and LLMs, we create synthetic bot agent personas, their tweets and their interactions, thereby simulating social media networks. We compare the generated networks against empirical bot/human data, observing that both network and linguistic properties of LLM-Powered Bots differ from Wild Bots/Humans. This has implications towards the detection and effectiveness of LLM-Powered Bots.
format Preprint
id arxiv_https___arxiv_org_abs_2508_00998
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Are LLM-Powered Social Media Bots Realistic?
Ng, Lynnette Hui Xian
Carley, Kathleen M.
Social and Information Networks
Artificial Intelligence
As Large Language Models (LLMs) become more sophisticated, there is a possibility to harness LLMs to power social media bots. This work investigates the realism of generating LLM-Powered social media bot networks. Through a combination of manual effort, network science and LLMs, we create synthetic bot agent personas, their tweets and their interactions, thereby simulating social media networks. We compare the generated networks against empirical bot/human data, observing that both network and linguistic properties of LLM-Powered Bots differ from Wild Bots/Humans. This has implications towards the detection and effectiveness of LLM-Powered Bots.
title Are LLM-Powered Social Media Bots Realistic?
topic Social and Information Networks
Artificial Intelligence
url https://arxiv.org/abs/2508.00998