seantw/DEBATE_LLM

DEBATE Submit Data – Human Conversation Datasets

This repository contains CSV files from the DEBATE project: large-scale human conversation experiments organized around controversial and opinion-based topics. The data consists of multi-round conversations between participants discussing political, social, and belief-related topics, following the protocol described in:

Chuang et al., “DEBATE: A Large-Scale Benchmark for Role-Playing LLM Agents in Multi-Agent, Long-Form Debates”,
39th Conference on Neural Information Processing Systems (NeurIPS 2025) Workshop: Scaling Environments for Agents (SEA),
arXiv preprint arXiv:2510.25110, 2025.

Paper Link: https://arxiv.org/pdf/2510.25110

Directory Structure

submit_data/
├── depth/                     # Phase 1: Depth topics (fewer topics, more conversations each)
│   ├── [topic_name]/         # Individual topic folders
│   │   ├── *.csv             # Conversation data files
│   │   └── ...
│   └── ...
├── breadth/                   # Phase 2: Breadth topics (many topics, fewer conversations each)
│   ├── [topic_name]/         # Individual topic folders
│   │   ├── *.csv             # Conversation data files
│   │   └── ...
│   └── ...
└── README.md                  # This file

Data Organization

Depth vs Breadth

• Depth Topics: Focused exploration of a smaller set of topics with multiple conversation sessions per topic
• Breadth Topics: Broad coverage across many different topics with fewer sessions per topic

Topic Categories

The conversations cover a wide range of controversial and opinion-based topics including:

Depth Topics (Phase 1)

• For more information on topics, check Appendix.

Breadth Topics (Phase 2)

• For more information on topics, check Appendix.

File Naming Convention

Each CSV file follows this naming pattern:

YYYYMMDD_HHMMSS_TOPIC_NAME_UNIQUE_ID_VERSION.csv

Where:

• YYYYMMDD: Date (Year/Month/Day)
• HHMMSS: Time (Hour/Minute/Second)
• TOPIC_NAME: Underscored topic description
• UNIQUE_ID: 26-character unique identifier
• VERSION: Version number (e.g., "0.0.1")

Data File Structure

Each CSV file contains conversation data with the following key columns:

• Event tracking: event_order, event_type
• Participants: worker_id, sender_id, recipient_id
• Content: text (messages, opinions, slider values)
• Conversation flow: chat_round_order, message_id
• User interaction: is_slider_changed (opinion rating changes)

Event Types

• Initial Opinion: Participant's starting position on the topic
• tweet: Short messages during conversation
• message_sent/message_received: Direct messages between participants

Special Notation

• [SLIDER_VALUE=X]: Indicates participant's opinion rating (typically 1-5 scale)
• [AUTOSUBMISSION DUE TO TIME LIMIT]: System-generated due to timeout

Data Usage

This dataset is suitable for research on:

• Opinion dynamics and persuasion
• Human-AI conversation patterns
• Political and social belief systems
• Argumentation and debate analysis
• Consensus building in controversial topics

Data Quality

• Files contain real human conversation data
• Some conversations may be incomplete due to participant dropout
• Time limits may have caused automatic submissions
• Processed data may contain empty rows: Consecutive messages from the same user are concatenated and treated as a single message, which can result in empty rows in the processed dataset

License & Usage Restrictions

This dataset is released under the:

DEBATE Dataset Research-Only License (Non-Commercial, v1.0) (see the LICENSE file in this repository).

Citation

Please cite the following work when using this dataset in your research:

@article{chuang2025debate,
  title={DEBATE: A Large-Scale Benchmark for Role-Playing LLM Agents in Multi-Agent, Long-Form Debates},
  author={Chuang, Yun-Shiuan and Tu, Ruixuan and Dai, Chengtao and Vasani, Smit and Yao, Binwei and Tessler, Michael Henry and Yang, Sijia and Shah, Dhavan V and Hawkins, Robert D and Hu, Junjie and others},
  journal={arXiv preprint arXiv:2510.25110},
  year={2025}
}