# Public Discourse Sandbox: Facilitating Human and AI Digital Communication Research

arXiv: https://arxiv.org/abs/2505.21604 · HTML: https://mlsanity.com/paper/2505.21604/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 32 references that are in the map.
- First posted on arXiv 27 May 2025.

## Builds on (most cited first, 7 of 7)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Bots increase exposure to negative and inflammatory content in online social systems](https://mlsanity.com/paper/1802.07292/) (2018)
- [Simulating Rumor Spreading in Social Networks using LLM Agents](https://mlsanity.com/paper/2502.01450/) (2025)
- [LLMs Among Us: Generative AI Participating in Digital Discourse](https://mlsanity.com/paper/2402.07940/) (2024)
- [Bots, #StrongerIn, and #Brexit: Computational Propaganda during the UK-EU Referendum](https://mlsanity.com/paper/1606.06356/) (2016)
- [Evidence of Complex Contagion of Information in Social Media: An Experiment Using Twitter Bots](https://mlsanity.com/paper/1703.06027/) (2017)
- [Social Media Bot Policies: Evaluating Passive and Active Enforcement](https://mlsanity.com/paper/2409.18931/) (2024)

## Abstract (arXiv)

Social media serves as a primary communication and information dissemination platform for major global events, entertainment, and niche or topically focused community discussions. Therefore, it represents a valuable resource for researchers who aim to understand numerous questions. However, obtaining data can be difficult, expensive, and often unreliable due to the presence of bots, fake accounts, and manipulated content. Additionally, there are ethical concerns if researchers decide to conduct an online experiment without explicitly notifying social media users about their intent. There is a need for more controlled and scalable mechanisms to evaluate the impacts of digital discussion interventions on audiences. We introduce the Public Discourse Sandbox (PDS), which serves as a digital discourse research platform for human-AI as well as AI-AI discourse research, testing, and training. PDS provides a safe and secure space for research experiments that are not viable on public, commercial social media platforms. Its main purpose is to enable the understanding of AI behaviors and the impacts of customized AI participants via techniques such as prompt engineering, retrieval-augmented generation (RAG), and fine-tuning. We provide a hosted live version of the sandbox to support researchers as well as the open-sourced code on GitHub for community collaboration and contribution.