This repository contains the dataset and the PyTorch code for 'CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems'.

We provide a novel dataset (referred to as CaSiNo) of 1030 negotiation dialogues. Two participants take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. This design keeps the task tractable, while still facilitating linguistically rich and personal conversations.

data: The complete CaSiNo dataset along with the strategy annotations.
strategy_prediction: Code for strategy prediction in a multi-task learning setup.

Participant Info

• Demographics (Age, Gender, Ethnicity, Education)
• Personality attributes (SVO and Big-5)
• Preference order
• Arguments for needing or not needing a specific item

Negotiation Dialogue

• Alternating conversation between two participants
• 11.6 utterances on average
• Includes the use of four emoticons: Joy, Sadness, Anger, Surprise

Negotiation Outcomes

• Points scored
• Satisfaction (How satisfied are you with the negotiation outcome?)
• Opponent Likeness (How much do you like your opponent?)

Strategy Annotations

• Utterance-level annotations for various negotiation strategies used by the participants
• Available for 396 dialogues (4615 utterances)

If you use data or code in this repository, please cite our paper:

@inproceedings{chawla2021casino,
  title={CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems},
  author={Chawla, Kushal and Ramirez, Jaysa and Clever, Rene and Lucas, Gale and May, Jonathan and Gratch, Jonathan},
  booktitle={Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  pages={3167--3185},
  year={2021}
}

Please refer to the LICENSE file in the root directory for more details.