Longitudinal Study on Social and Emotional Use of AI Conversational Agent
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Abstract (arXiv)
Development in digital technologies has continuously reshaped how individuals seek and receive social and emotional support. While online platforms and communities have long served this need, the increased integration of general-purpose conversational AI into daily lives has introduced new dynamics in how support is provided and experienced. Existing research has highlighted both benefits (e.g., wider access to well-being resources) and potential risks (e.g., over-reliance) of using AI for support seeking. In this five-week, exploratory study, we recruited 149 participants divided into two usage groups: a baseline usage group (BU, n=60) that used the internet and AI as usual, and an active usage group (AU, n=89) encouraged to use one of four commercially available AI tools (Microsoft Copilot, Google Gemini, PI AI, ChatGPT) for social and emotional interactions. Our analysis revealed significant increases in perceived attachment towards AI (32.99 percentage points), perceived AI empathy (25.8 p.p.), and motivation to use AI for entertainment (22.90 p.p.) among the AU group. We also observed that individual differences (e.g., gender identity, prior AI usage) influenced perceptions of AI empathy and attachment. Lastly, the AU group expressed higher comfort in seeking personal help, managing stress, obtaining social support, and talking about health with AI, indicating potential for broader emotional support while highlighting the need for safeguards against problematic usage. Overall, our exploratory findings underscore the importance of developing consumer-facing AI tools that support emotional well-being responsibly, while empowering users to understand the limitations of these tools.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 6 of its 70 references that are in the map. First posted on arXiv 19 Apr 2025.
Builds on
6 of 70 references.
References · 6
- 2023GPT-4 Technical Reportcited by 18,396
- 2022Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goalscited by 126
- 2023Understanding the Benefits and Challenges of Using Large Language Model-based Conversational Agents for Mental Well-being Supportcited by 75
- 2023The Dangers of trusting Stochastic Parrots: Faithfulness and Trust in Open-domain Conversational Question Answeringcited by 26
- 2024From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agentscited by 25
- 2023Chatbots as social companions: How people perceive consciousness, human likeness, and social health benefits in machinescited by 17
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Citing papers per year: 2025: 4; 2026: 6.
10 papers.
- 2025A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism and Its Mediating Role on Social Impactscited by 10
- 2026AI Chatbot Suicide Risk Detection and Response: Human Validation Study of the Open-Source VERA-MH Safety Evaluationcited by 4
- 2025LLM-D12: A Dual-Dimensional Scale of Instrumental and Relational Dependencies on Large Language Modelscited by 3
- 2025Detecting and Preventing Harmful Behaviors in AI Companions: Development and Evaluation of the SHIELD Supervisory Systemcited by 3
- 2026AI as Entertainmentcited by 2
- 2025The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbotscited by 1
- 2026Adopt neq Adapt: Longitudinal Analyses of LLM Conversations in the Wildcited by 1
- 2026Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connectioncited by 0
- 2026Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Studycited by 0
- 2026Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptionscited by 0
- 2026Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions15 Sep 2026
- 2026Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study13 Sep 2026
- 2026Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connection2 Jun 2026
- 2026Adopt neq Adapt: Longitudinal Analyses of LLM Conversations in the Wild27 May 2026
- 2026AI Chatbot Suicide Risk Detection and Response: Human Validation Study of the Open-Source VERA-MH Safety Evaluation4 Feb 2026
- 2026AI as Entertainment13 Jan 2026
- 2025A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism and Its Mediating Role on Social Impacts23 Sep 2025
- 2025The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbots16 Sep 2025
- 2025Detecting and Preventing Harmful Behaviors in AI Companions: Development and Evaluation of the SHIELD Supervisory System8 Sep 2025
- 2025LLM-D12: A Dual-Dimensional Scale of Instrumental and Relational Dependencies on Large Language Models7 Jun 2025