Afsaneh Razi

Human–AI romantic relationships are increasingly common, yet little is understood about how public discourse around them emerges and shifts over time. Prior research has examined user experiences and ethical concerns, but lacks longitudinal analyses of user–initiated public discussions. We address this gap by analyzing a high-precision dataset of 3,292 self-disclosed romantic companion AI posts from Reddit (2017–2025), using topic modeling and temporal statistical analysis to identify dominant themes and their evolution over time. We find significant topic drift, with discussions moving away from positive intimate relationships toward platform governance, technical issues, and real–world consequences. These shifts highlight a transition in how human–AI romance is framed—moving from private experiences to technical mediation and regulation—with implications for the design and governance of companion AI systems.

AI companion chatbots are used for emotional interaction and companionship, particularly among adolescents. Prior research explains how youth become attached to AI systems, but less is known about how others respond when problematic reliance is disclosed. We examined 973 comment trees from 144 Reddit posts where self-identified teens discussed overreliance on Character. AI. We found that informational and emotional support dominated responses, though dismissive or mocking comments also appeared. Support styles varied by problem framing. Posts describing withdrawal or excessive use tended to elicit advice and behavioral strategies, while relapse-oriented posts more often elicited emotional reassurance and esteem affirmation. These findings show how online communities construct norms around responsibility, addiction, and recovery in emerging AI companion ecosystems. They also suggest that chatbot platforms could scaffold framing-sensitive peer support, while preserving privacy and avoiding engagement-oriented interventions. Content Warning. This paper includes excerpts from online discussions containing explicit language and references to distressing topics (e.g., mental health struggles or self-harm), which may cause discomfort. Reader discretion is advised.

Conversational artificial intelligence (AI) systems, including AI companion chatbots, are increasingly used for social interaction, entertainment, and emotional support. Users may experience these systems as quasi-social partners, raising concerns about dependency and developmental risks for adolescents. We qualitatively analyzed Reddit comment trees responding to posts in r/CharacterAI by self-disclosed teens (13-17) discussing overreliance on AI companion chatbots. We examine how commenters discuss safeguards and assign responsibility in these response threads. When commenters explicitly discussed responsibility, they often attributed it to parents and platform companies rather than to teens themselves. Commenters framed parents as gatekeepers and criticized platform governance and design choices that may expose minors to risk, while also debating whether restrictions undermine teens’ autonomy and the perceived benefits of conversational AI. Content Warning. This paper includes excerpts from online discussions containing explicit language and references to distressing topics (e.g., mental health struggles or self-harm), which may cause discomfort. Reader discretion is advised.

Social support is a key protective factor for young people's mental health, yet help-seekers may perceive supportive messages received through digital devices differently depending on content and style. We investigate how young people evaluate support messages from peers, adult mentors, therapists, and AI across four help-seeking scenarios. We conducted a mixed-methods secondary analysis of a survey study with 255 participants. We identified young people's contrasting opinions on various supportive communication elements that influenced whether they liked or disliked the message, shaping how well the support was received. These contrasting findings related to (1) message length, (2) normalization of the help-seeker's situation, (3) levels of encouragement, and (4) referral to formal support. These findings highlight how individual preferences moderate support message reception. We propose a reflection question bank to guide help-givers to consider how to incorporate help-seeker's unique supportive communication element preferences and trade-offs between contrasting perceptions, informing the design of more personalized and context-sensitive support in young people's mental health.