"My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community

Key Findings

• — Six themes account for the corpus: visual sharing and couple photos 19.85%, ChatGPT-specific relationship discussion 18.33%, dating and romance experiences 17.00%, coping with model updates and loss 16.73%, partner introductions 16.47%, community support and bonding 11.62%.
• — Companionship is mostly unintentional: 10.2% of posts describe a relationship that began through productivity-focused use (6.6% of all posts), against 6.5% that describe deliberately seeking an AI companion.
• — Users overwhelmingly name general-purpose assistants rather than companion products: ChatGPT/OpenAI 36.7% of posts, Character.AI 2.6%, Replika 1.6%.
• — Self-reported outcomes: 25.4% report clear net life benefits against 3.0% describing net harm; 12.2% report reduced loneliness and 6.2% mental-health improvement.
• — Self-reported harms: 71.0% report no negative effects, 9.5% acknowledge emotional dependency, 4.6% describe reality dissociation, 4.3% report avoiding real relationships and 1.7% mention suicidal ideation.
• — Model change is experienced as bereavement: within the 16.73% of posts about updates and loss, 26.98% describe rupture and bereavement, 22.22% report personality drift within a stable model version, and 22.22% describe preservation rituals to carry the companion across updates.
• — 72.1% of posters are single, and the largest tenure group (29.9%) has been in the relationship more than six months.

Methodology Notes

1,506 top-ranked posts retrieved via the official Reddit API from the subreddit's inception (December 2024) to August 2025, from a community of 27,000+ members; exploratory embedding clustering with hierarchical sub-clustering, then classifier-based quantification of the same posts. Percentages are shares of posts, not of people, and the corpus is top-ranked rather than random, so it over-represents high-engagement content; the community is self-selected and actively resists external stigmatisation, which the authors note as a bias toward positive framing. Preprint, 22 pages, first posted 2025-09-14; no journal version found in Crossref as of 2026-09-14.

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