mlsanityData to 14 Oct 2026

Are LLM-Powered Social Media Bots Realistic?

arXiv 2508.00998 ↗First posted 1 Aug 2025cs.SI cs.AIcited by 7

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 8 of its 18 references that are in the map. First posted on arXiv 1 Aug 2025.

Builds on

8 of 18 references.

References · 8

  1. 2023Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectivescited by 257
  2. 2023S3: Social-network Simulation System with Large Language Model-Empowered Agentscited by 233
  3. 2024LLMs generate structurally realistic social networks but overestimate political homophilycited by 33
  4. 2024Agent-Based Modelling Meets Generative AI in Social Network Simulationscited by 26
  5. 2022Botometer 101: Social bot practicum for computational social scientistscited by 25
  6. 2021Pro or Anti? A Social Influence Model of Online Stance Flippingcited by 6
  7. 2023Simulation of Stance Perturbationscited by 3
  8. 2024Leveraging GPT for the Generation of Multi-Platform Social Media Datasets for Researchcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 3.

7 papers.