Tracking how people talk about AI companions

Themes emerge from direct observation of how people talk in these communities — patterns in language that signal recurring concerns, experiences, and framings. For each theme, we identify candidate keywords: terms and phrases that appear to reliably mark that theme in context.

• 💕 Romance — Language of love, dating, and romantic attachment
• 🔞 Sex / ERP — Language of sexual and erotic roleplay
• 🧠 Consciousness — Language of sentience, awareness, and inner experience
• 🫂 Therapy — Language of mental health support and emotional care
• 💊 Addiction — Language of dependency and compulsion
• 🥀 Rupture — Language of loss and grief

Each keyword is then validated through manual scoring of 100-post samples, checking whether the term actually signals the theme or just happens to co-occur. Keywords scoring 80% precision or above are accepted. Keywords in the 60–79% range may be accepted when false positive patterns are well-defined and the keyword adds meaningful vocabulary diversity. All validation decisions are documented and available on the GitHub repository.

The chart shows how often these validated terms are mentioned per 1,000 posts, using a 7-day rolling average to smooth daily noise. Because we normalize to post volume, the trends reflect changes in how people talk — not just growth in the communities themselves.

A theme's mention rate reflects how often people use distinctive, validated language for that topic — not how prevalent the topic is overall.

Some themes have highly specific vocabulary. When someone describes AI addiction, they borrow clinical recovery language: “relapse,” “cold turkey,” “chatbot addiction.” These terms are rare outside that context and validate at near-perfect precision. The keyword net catches most of what's there.

Other themes are expressed through everyday language. When someone is in a romantic relationship with their AI, they say “I love him,” “my boyfriend,” “we went on a date” — words that are indistinguishable from how people talk about human relationships. These fail precision validation because they can't be reliably attributed to AI companionship. Only highly specific phrases like “our wedding” or “my AI partner” survive, meaning the keyword net captures only a fraction of the actual romance discourse.

The result: addiction may show a higher mention rate than romance, but that reflects vocabulary distinctiveness, not phenomenon size. Each theme's trend line is meaningful over time — a spike or decline in a theme tells you something real about how that conversation is changing. But comparing mention rates between themes does not tell you which topic is “bigger” or more important.