MUDiC: A Dataset for Multi-User Dialogue and Collaboration in Chatbot Interaction

We introduce MUDiC, a novel dataset on task-based multi-user interactions in chatbots. Unlike most traditional dialogue corpora that focus on one-to-one human–chatbot exchanges, this dataset captures conversations involving two human participants engaging with a single system. The data include diverse conversational contexts such as shared group task, user intents, and mechanisms to deal with off-topic talk. MUDiC consists of 1,689 dialogue exchanges between 20 groups and the chatbot. Each session is annotated with user id, interaction turns, and intents and dialogue acts, enabling an analysis of group conversational dynamics. Consequently, the dataset aims to support tasks such as multi-user dialogue modelling, intent disambiguation, and moderation behaviour, which are relevant factors for the design of socially aware chatbots.

本研究提出MUDiC，一款面向聊天机器人任务型多用户交互的新型数据集。与绝大多数聚焦于人机一对一交互的传统对话语料库不同，本数据集收录的是两名人类用户与单一系统开展交互的对话内容。该数据集涵盖丰富的对话场景，包括协作式群组任务、用户意图以及跑题对话的处理机制。MUDiC共包含20个用户群组与聊天机器人之间的1689轮对话交互。每一段对话会话均标注了用户ID、交互轮次、意图以及对话行为，可支撑对群组对话动态特征的分析研究。因此，本数据集可服务于多用户对话建模、意图消歧、审核行为等研究任务，这些均为设计具备社交感知能力的聊天机器人的核心考量因素。