ChatGPT Role-play Dataset: Analysis of User Motives and Model
  Naturalness
Yufei Tao Ameeta Agrawal Judit Dombi Tetyana Sydorenko Jung In Lee
Recent advances in interactive large language models like ChatGPT have
revolutionized various domains; however, their behavior in natural and
role-play conversation settings remains underexplored. In our study, we address
this gap by deeply investigating how ChatGPT behaves during conversations in
different settings by analyzing its interactions in both a normal way and a
role-play setting. We introduce a novel dataset of broad range of human-AI
conversations annotated with user motives and model naturalness to examine (i)
how humans engage with the conversational AI model, and (ii) how natural are AI
model responses. Our study highlights the diversity of user motives when
interacting with ChatGPT and variable AI naturalness, showing not only the
nuanced dynamics of natural conversations between humans and AI, but also
providing new avenues for improving the effectiveness of human-AI
communication.