# ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents

arXiv: https://arxiv.org/abs/2410.20746 · HTML: https://mlsanity.com/paper/2410.20746/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 70 references that are in the map.
- First posted on arXiv 28 Oct 2024.

## Builds on (most cited first, 27 of 27)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework](https://mlsanity.com/paper/2308.00352/) (2023)
- [Improving Factuality and Reasoning in Language Models through Multiagent Debate](https://mlsanity.com/paper/2305.14325/) (2023)
- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://mlsanity.com/paper/2309.07864/) (2023)
- [ChatDev: Communicative Agents for Software Development](https://mlsanity.com/paper/2307.07924/) (2023)
- [Large Language Model based Multi-Agents: A Survey of Progress and Challenges](https://mlsanity.com/paper/2402.01680/) (2024)
- [Character-LLM: A Trainable Agent for Role-Playing](https://mlsanity.com/paper/2310.10158/) (2023)
- [Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives](https://mlsanity.com/paper/2312.11970/) (2023)
- [RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models](https://mlsanity.com/paper/2310.00746/) (2023)
- [The Political Preferences of LLMs](https://mlsanity.com/paper/2402.01789/) (2024)
- [Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation](https://mlsanity.com/paper/2402.16333/) (2024)
- [Can Large Language Model Agents Simulate Human Trust Behavior?](https://mlsanity.com/paper/2402.04559/) (2024)
- [Network Formation and Dynamics Among Multi-LLMs](https://mlsanity.com/paper/2402.10659/) (2024)
- [Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks](https://mlsanity.com/paper/2407.09893/) (2024)
- [Identity-Driven Hierarchical Role-Playing Agents](https://mlsanity.com/paper/2407.19412/) (2024)
- [Social physics](https://mlsanity.com/paper/2110.01866/) (2021)
- [Large Language Model-driven Multi-Agent Simulation for News Diffusion Under Different Network Structures](https://mlsanity.com/paper/2410.13909/) (2024)
- [Modelling Political Coalition Negotiations Using LLM-based Agents](https://mlsanity.com/paper/2402.11712/) (2024)
- [SoMeLVLM: A Large Vision Language Model for Social Media Processing](https://mlsanity.com/paper/2402.13022/) (2024)
- [Correcting Sociodemographic Selection Biases for Population Prediction from Social Media](https://mlsanity.com/paper/1911.03855/) (2019)
- [Representation Bias in Political Sample Simulations with Large Language Models](https://mlsanity.com/paper/2407.11409/) (2024)
- [Computational Agent-based Models in Opinion Dynamics: A Survey on Social Simulations and Empirical Studies](https://mlsanity.com/paper/2306.03446/) (2023)
- [140 Characters to Victory?: Using Twitter to Predict the UK 2015 General Election](https://mlsanity.com/paper/1505.01511/) (2015)
- [Can LLMs Help Predict Elections? (Counter)Evidence from the World's Largest Democracy](https://mlsanity.com/paper/2405.07828/) (2024)
- [Language Evolution for Evading Social Media Regulation via LLM-based Multi-agent Simulation](https://mlsanity.com/paper/2405.02858/) (2024)
- [AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models](https://mlsanity.com/paper/2410.07561/) (2024)

## Built on by (most cited first, 30 of 35)

- [AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society](https://mlsanity.com/paper/2502.08691/) (2025)
- [Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems](https://mlsanity.com/paper/2504.01990/) (2025)
- [From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents](https://mlsanity.com/paper/2412.03563/) (2024)
- [SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users](https://mlsanity.com/paper/2504.10157/) (2025)
- [Know You First and Be You Better: Modeling Human-Like User Simulators via Implicit Profiles](https://mlsanity.com/paper/2502.18968/) (2025)
- [LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios](https://mlsanity.com/paper/2508.17692/) (2025)
- [How Far are LLMs from Being Our Digital Twins? A Benchmark for Persona-Based Behavior Chain Simulation](https://mlsanity.com/paper/2502.14642/) (2025)
- [From Selection to Generation: A Survey of LLM-based Active Learning](https://mlsanity.com/paper/2502.11767/) (2025)
- [The PIMMUR Principles: Ensuring Validity in Collective Behavior of LLM Societies](https://mlsanity.com/paper/2509.18052/) (2025)
- [MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework](https://mlsanity.com/paper/2504.21582/) (2025)
- [AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need](https://mlsanity.com/paper/2506.15451/) (2025)
- [YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models](https://mlsanity.com/paper/2505.07581/) (2025)
- [A Large-Scale Simulation on Large Language Models for Decision-Making in Political Science](https://mlsanity.com/paper/2412.15291/) (2024)
- [PIORS: Personalized Intelligent Outpatient Reception based on Large Language Model with Multi-Agents Medical Scenario Simulation](https://mlsanity.com/paper/2411.13902/) (2024)
- [Modeling Earth-Scale Human-Like Societies with One Billion Agents](https://mlsanity.com/paper/2506.12078/) (2025)
- [Large Language Models in Politics and Democracy: A Comprehensive Survey](https://mlsanity.com/paper/2412.04498/) (2024)
- [Can ChatGPT Really Understand Modern Chinese Poetry?](https://mlsanity.com/paper/2603.20851/) (2026)
- [NegotiationGym: Self-Optimizing Agents in a Multi-Agent Social Simulation Environment](https://mlsanity.com/paper/2510.04368/) (2025)
- [AI Agents Alone Are Not (Yet) Sufficient for Social Simulation](https://mlsanity.com/paper/2603.00113/) (2026)
- [LLM Agents as Social Scientists: A Human-AI Collaborative Platform for Social Science Automation](https://mlsanity.com/paper/2604.01520/) (2026)
- [Computational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agents](https://mlsanity.com/paper/2508.17366/) (2025)
- [Enhancing Persona Following at Decoding Time via Dynamic Importance Estimation for Role-Playing Agents](https://mlsanity.com/paper/2603.01438/) (2026)
- [Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changes](https://mlsanity.com/paper/2508.08837/) (2025)
- [The Hunger Game Debate: On the Emergence of Over-Competition in Multi-Agent Systems](https://mlsanity.com/paper/2509.26126/) (2025)
- [Mitigating Social Desirability Bias in Random Silicon Sampling](https://mlsanity.com/paper/2512.22725/) (2025)
- [Uncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation](https://mlsanity.com/paper/2606.30395/) (2026)
- [Persona-driven Simulation of Voting Behavior in the European Parliament with Large Language Models](https://mlsanity.com/paper/2506.11798/) (2025)
- [ToMPO: Training LLM Strategic Decision Making from a Multi-Agent Perspective](https://mlsanity.com/paper/2509.21134/) (2025)
- [What AI Speaks for Your Community: Polling AI Agents for Public Opinion on Data Center Projects](https://mlsanity.com/paper/2511.22037/) (2025)
- [FlockVote: LLM-Empowered Agent-Based Modeling for Simulating U.S. Presidential Elections](https://mlsanity.com/paper/2512.05982/) (2025)

## Abstract (arXiv)

The massive population election simulation aims to model the preferences of specific groups in particular election scenarios. It has garnered significant attention for its potential to forecast real-world social trends. Traditional agent-based modeling (ABM) methods are constrained by their ability to incorporate complex individual background information and provide interactive prediction results. In this paper, we introduce ElectionSim, an innovative election simulation framework based on large language models, designed to support accurate voter simulations and customized distributions, together with an interactive platform to dialogue with simulated voters. We present a million-level voter pool sampled from social media platforms to support accurate individual simulation. We also introduce PPE, a poll-based presidential election benchmark to assess the performance of our framework under the U.S. presidential election scenario. Through extensive experiments and analyses, we demonstrate the effectiveness and robustness of our framework in U.S. presidential election simulations.