DeliData: A Dataset for Deliberation in Multi-party Problem Solving

Author:

Karadzhov Georgi1ORCID,Stafford Tom2ORCID,Vlachos Andreas1ORCID

Affiliation:

1. University of Cambridge, Cambridge, United Kingdom

2. University of Sheffield, Sheffield, United Kingdom

Abstract

Group deliberation enables people to collaborate and solve problems, however, it is understudied due to a lack of resources. To this end, we introduce the first publicly available dataset containing collaborative conversations on solving a well-established cognitive task, consisting of 500 group dialogues and 14k utterances. In 64% of these conversations, the group members are able to find a better solution than they had identified individually, and in 43.8% of the groups who had a correct answer as their final solution, none of the participants had solved the task correctly by themselves. Furthermore, we propose a novel annotation schema that captures deliberation cues and release all 14k utterances annotated with it. Finally, we use the proposed dataset to develop and evaluate two methods for generating deliberation utterances. The data collection platform, dataset and annotated corpus are publicly available at https://delibot.xyz.

Funder

ESPRC Doctoral Training Scholarship

ESPRC

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

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