A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism and Its Mediating Role on Social Impacts
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Abstract (arXiv)
Many Large Language Model (LLM) chatbots are designed and used for companionship, and people have reported forming friendships, mentorships, and romantic partnerships with them. Concerns that companion chatbots may harm or replace real human relationships have been raised, but whether and how these social consequences occur remains unclear. In the present longitudinal study (N = 183), participants were randomly assigned to a chatbot condition (text chat with a companion chatbot) or to a control condition (text-based word games) for 10 minutes a day for 21 days. Participants also completed four surveys during the 21 days and engaged in audio recorded interviews on day 1 and 21. Overall, social health and relationships were not significantly impacted by companion chatbot interactions across 21 days of use. However, a detailed analysis showed a different story. People who had a higher desire to socially connect also tended to anthropomorphize the chatbot more, attributing humanlike properties to it; and those who anthropomorphized the chatbot more also reported that talking to the chatbot had a greater impact on their social interactions and relationships with family and friends. Via a mediation analysis, our results suggest a key mechanism at work: the impact of human-AI interaction on human-human social outcomes is mediated by the extent to which people anthropomorphize the AI agent, which is in turn motivated by a desire to socially connect. In a world where the desire to socially connect is on the rise, this finding may be cause for concern.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 2 of its 52 references that are in the map. First posted on arXiv 23 Sep 2025.
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2 of 52 references.
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Citing papers per year: 2026: 10.
10 papers.
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- 2026Understanding Persuasive Interactions between Generative Social Agents and Humans: The Knowledge-based Persuasion Model (KPM)cited by 3
- 2026Synergy: A Next-Generation General-Purpose Agent for Open Agentic Webcited by 2
- 2026Anthropomorphism and Trust in Human-Large Language Model interactionscited by 2
- 2026Alignment Is Not Enough: A Relational Framework for Moral Standing in Human-AI Interactioncited by 1
- 2026Unilateral Relationship Revision Power in Human-AI Companion Interactioncited by 1
- 2026The Illusion of Friendship: Why Generative AI Demands Unprecedented Ethical Vigilancecited by 0
- 2026Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modelingcited by 0
- 2026Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactionscited by 0
- 2026Generative AI Alignment with Hinduism's Theological Plurality and Sacred Representationcited by 0
- 2026Generative AI Alignment with Hinduism's Theological Plurality and Sacred Representation28 Aug 2026
- 2026Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions3 Aug 2026
- 2026Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling15 May 2026
- 2026Synergy: A Next-Generation General-Purpose Agent for Open Agentic Web30 Mar 2026
- 2026Unilateral Relationship Revision Power in Human-AI Companion Interaction24 Mar 2026
- 2026Anthropomorphism and Trust in Human-Large Language Model interactions1 Mar 2026
- 2026Alignment Is Not Enough: A Relational Framework for Moral Standing in Human-AI Interaction13 Feb 2026
- 2026Understanding Persuasive Interactions between Generative Social Agents and Humans: The Knowledge-based Persuasion Model (KPM)12 Feb 2026
- 2026Belief Offloading in Human-AI Interaction9 Feb 2026
- 2026The Illusion of Friendship: Why Generative AI Demands Unprecedented Ethical Vigilance12 Jan 2026