mlsanityData to 7 Oct 2026

TrendSim: Simulating Trending Topics in Social Media Under Poisoning Attacks with LLM-based Multi-agent System

arXiv 2412.12196 ↗First posted 14 Dec 2024cs.SI cs.AIcited by 6

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Trending topics have become a significant part of modern social media, attracting users to participate in discussions of breaking events. However, they also bring in a new channel for poisoning attacks, resulting in negative impacts on society. Therefore, it is urgent to study this critical problem and develop effective strategies for defense. In this paper, we propose TrendSim, an LLM-based multi-agent system to simulate trending topics in social media under poisoning attacks. Specifically, we create a simulation environment for trending topics that incorporates a time-aware interaction mechanism, centralized message dissemination, and an interactive system. Moreover, we develop LLM-based human-like agents to simulate users in social media, and propose prototype-based attackers to replicate poisoning attacks. Besides, we evaluate TrendSim from multiple aspects to validate its effectiveness. Based on TrendSim, we conduct simulation experiments to study four critical problems about poisoning attacks on trending topics for social benefit.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 14 of its 24 references that are in the map. First posted on arXiv 14 Dec 2024.

Builds on

14 of 24 references.

References · 14

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
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2 more
  1. 2023The SocialAI School: Insights from Developmental Psychology Towards Artificial Socio-Cultural Agentscited by 24
  2. 2018Preventing Poisoning Attacks on AI based Threat Intelligence Systemscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 2.

6 papers.

  1. 2025MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Frameworkcited by 12
  2. 2025The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societiescited by 12
  3. 2025YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Modelscited by 11
  4. 2026LLM Agents as Social Scientists: A Human-AI Collaborative Platform for Social Science Automationcited by 3
  5. 2025DynamiX: Large-Scale Dynamic Social Network Simulatorcited by 2
  6. 2026LLMs for Social Network Modeling: From Network Generation to Dynamic Processescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Simulating Rumor Spreading in Social Networks using LLM Agents
  2. 2024Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities
  3. 2024Large Language Model-driven Multi-Agent Simulation for News Diffusion Under Different Network Structures
  4. 2025Personalized Attacks of Social Engineering in Multi-turn Conversations: LLM Agents for Simulation and Detection
  5. 2025Towards Operational Validation of LLM-Agent Social Simulations: A Replicated Study of a Reddit-like Technology Forum
  6. 2026Can LLM Agents Simulate Dynamic Networks? A Case Study on Email Networks with Phishing Synthesis
  7. 2026Don't Trust Stubborn Neighbors: A Security Framework for Agentic Networks
  8. 2026MiroBench: Benchmarking Realism in Agentic Simulation of Real-world Discussions