Key points are not available for this paper at this time.
As the popularity of AI-powered chatbots has grown, research on supportive communication has begun to explore chatbots' ability to provide social support. This two-study project examined if humans and ChatGPT detect linguistic variations in support-seeking messages (levels of self-disclosure, Study 1; linguistic agency and causality, Study 2) and how message variations affect quality of support provided. ChatGPT responses were higher in interaction involvement and politeness, but human responses demonstrated more reciprocal self-disclosure. In Study 1, depth of self-disclosure influenced quality of human responses, but not ChatGPT responses. In Study 2, human responses were relatively consistent across variations in linguistic agency and causality, but ChatGPT responses demonstrated greater cognitive and emotional involvement to messages identifying non-biological causes of depression. Our findings suggest that ChatGPT can provide quality support for various stressors, but it is less able to adapt to nuances of how users describe their experiences compared to human support providers.
Hwang et al. (2025) studied this question.