"You tell me": A Dataset of GPT-4-Based Behaviour Change Support Conversations
CoRR(2024)
Abstract
Conversational agents are increasingly used to address emotional needs on top
of information needs. One use case of increasing interest are counselling-style
mental health and behaviour change interventions, with large language model
(LLM)-based approaches becoming more popular. Research in this context so far
has been largely system-focused, foregoing the aspect of user behaviour and the
impact this can have on LLM-generated texts. To address this issue, we share a
dataset containing text-based user interactions related to behaviour change
with two GPT-4-based conversational agents collected in a preregistered user
study. This dataset includes conversation data, user language analysis,
perception measures, and user feedback for LLM-generated turns, and can offer
valuable insights to inform the design of such systems based on real
interactions.
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