Year: 2023
Type: conference-paper
Abstract: Artificial intelligence (AI)-based systems, such as AI companions, have been increasingly used to meet the needs of individuals who experience loneliness. In this current study, we sought to identify the mechanism underlying human-AI interactions in the mental health context. We use a Latent Dirichlet Allocation (LDA) approach to analyze a sample of user-generated content consisting of rich data on AI companion app’s reviews over a two-year period. We extracted five positive topics (i.e., perceived humanness, perceived emotional support, perceived AI’s friendship, perceived (less) loneliness, and mental health benefits) and four negative topics (i.e., perceived lack of conscientiousness, perceived incredibility, perceived violation of privacy, and perceived creepiness of AI) from our analysis. Our AI-based emotional support model suggests that these positive and negative characteristics are interrelated. Our study provides an understanding of the relationship between AI companions and human users in light of research showing the effectiveness of an AI-based intervention for mental health care.
Institutions: Baylor University, TBS Education
Language: English
Subfield: Applied Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4391904058