Combating Loneliness with Artificial Intelligence: An AI-Based Emotional Support Model
Open accessAbstract
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.
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The appeal of AI agents as companions lies in their consistency and perceived non-judgmentality.
“The appeal of AI agents as companions lies in their consistency and perceived non-judgmentality [27, 40, 55]”
From Emotional Coregulation in Close Relationships with AI Agents: A Survey of ChatGPT and Replika Users (2025) · cites this paper as [55]
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Emotional Coregulation in Close Relationships with AI Agents: A Survey of ChatGPT and Replika Users
Pruss, E., Alimardani, M., Struijs, S., & Koole, S. L. (2025) · Proceedings of the 13th International Conference on Human-Agent Interaction · doi:10.1145/3765766.3765801 · Cited by 4 · see citing works
“The appeal of AI agents as companions lies in their consistency and perceived non-judgmentality [27, 40, 55], but these same features may also limit their capacity for mutual growth or challenge; elements that often define human relationships.”
- Authors
- Sullivan, Y., Nyawa, S., & Fosso Wamba, S.
- Affiliations
- Baylor University (US)
- TBS Education (FR)
- Venue
- Proceedings of the Annual Hawaii International Conference on System Sciences
- Published
- 2023
- ISSN
- 1530-1605 (ISSN-L)
- 2572-6862
- OpenAlex
- W4391904058
- Cited by
- 44
- References
- 14
- Citations by year
- 2026: 18 · 2025: 16 · 2024: 9 · 2023: 1
- FWCI
- 19.37
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Hawaii International Conference on System Sciences (HICSS) (publishedVersion, cc-by-nc-nd)
- Journal of the Association for Information Systems (submittedVersion)
- ScholarSpace (University of Hawaii at Manoa) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- loneliness, AI companions, human-AI interaction, emotional support, mental health, perceived humanness, privacy violations, AI-based interventions
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