mlsanityData to 7 Oct 2026

AI Companions Reduce Loneliness

arXiv 2407.19096 ↗First posted 9 Jul 2024cs.CY cs.AIcited by 28

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Abstract (arXiv)

Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are effective at alleviating loneliness. We address this question by focusing on AI companions applications designed to provide consumers with synthetic interaction partners. Studies 1 and 2 find suggestive evidence that consumers use AI companions to alleviate loneliness, by employing a novel methodology for fine tuning large language models to detect loneliness in conversations and reviews. Study 3 finds that AI companions successfully alleviate loneliness on par only with interacting with another person, and more than other activities such watching YouTube videos. Moreover, consumers underestimate the degree to which AI companions improve their loneliness. Study 4 uses a longitudinal design and finds that an AI companion consistently reduces loneliness over the course of a week. Study 5 provides evidence that both the chatbots' performance and, especially, whether it makes users feel heard, explain reductions in loneliness. Study 6 provides an additional robustness check for the loneliness alleviating benefits of AI companions.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 5 of its 67 references that are in the map. First posted on arXiv 9 Jul 2024.

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5 of 67 references.

References · 5

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022A Holistic Approach to Undesired Content Detection in the Real Worldcited by 337
  3. 2021Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasetscited by 179
  4. 2019How should my chatbot interact? A survey on human-chatbot interaction designcited by 56
  5. 2020Sentiment Analysis Based on Deep Learning: A Comparative Studycited by 37

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 10; 2026: 17.

28 papers.

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  1. 2025A Pragmatic View of AI Personhoodcited by 12
  2. 2025Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Theorycited by 8
  3. 2024The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AIcited by 6
  4. 2026PTCBENCH: Benchmarking Contextual Stability of Personality Traits in LLM Systemscited by 4
  5. 2025Mental Models of Autonomy and Sentience Shape Reactions to AIcited by 3
  6. 2025Revisiting Trust in the Era of Generative AI: Factorial Structure and Latent Profilescited by 2
  7. 2025"I am here for you": How relational conversational AI appeals to adolescents, especially those who are socially and emotionally vulnerablecited by 2
  8. 2026Privacy in Human-AI Romantic Relationships: Concerns, Boundaries, and Agencycited by 2
  9. 2026Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountabilitycited by 2
  10. 2025Conceptualization, Operationalization, and Measurement of Machine Companionship: A Scoping Reviewcited by 1
  11. 2025The Adaptation Paradox: Agency vs. Mimicry in Companion Chatbotscited by 1
  12. 2025Making LLMs Reliable When It Matters Most: A Five-Layer Architecture for High-Stakes Decisionscited by 1
16 more
  1. 2025AI for Proactive Mental Health: A Multi-Institutional, Longitudinal, Randomized Controlled Trialcited by 1
  2. 2026Not a Silver Bullet for Loneliness: How Attachment and Age Shape Intimacy with AI Companionscited by 1
  3. 2026CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Productioncited by 1
  4. 2026Discourse Diversity in Multi-Turn Empathic Dialoguecited by 1
  5. 2026Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaborationcited by 1
  6. 2025The Cost-Benefit of Interdisciplinarity in AI for Mental Healthcited by 0
  7. 2026When Nobody Around Is Real: Exploring Public Opinions and User Experiences On the Multi-Agent AI Social Platformcited by 0
  8. 2026When Workout Buddies Are Virtual: AI Agents and Human Peers in a Longitudinal Physical Activity Studycited by 0
  9. 2026VET: A Framework for Analyzing AI Discoursecited by 0
  10. 2026Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connectioncited by 0
  11. 2026AICompanionBench: Benchmarking LLMs-as-Judges for AI Companion Safetycited by 0
  12. 2026Aesthetic Perspectives in Information Systems Research: A Hermeneutic Analysiscited by 0
  13. 2026AI Companions as Hyper Attachment and Caregiving Targetscited by 0
  14. 2026Me and My Bot: What Users Talk About in AI Companion Communities on Redditcited by 0
  15. 2026Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptionscited by 0
  16. 2026AnthroDial: Benchmarking LLM Anthropomorphism in Autonomous Social Interactioncited by 0