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

• The paper documents both potential psychosocial benefits and concerns including emotional dependence and social withdrawal in AI-companion use.Prior work cited in the introduction reports both mitigation of perceived isolation and risks such as dependence and withdrawal from human connections.Source: §1 · p. 2
• The field lacks large-scale empirical analyses of naturally occurring AI-companion communities, limiting understanding of how these relationships emerge, evolve, and affect users in real-world contexts.Source: §1 · p. 2
• The study analyzes 1,506 posts from r/MyBoyfriendIsAI using exploratory qualitative analysis and classifiers to examine themes, relationship characteristics, and user impacts.Source: §1 · p. 2
• The paper maps experiences including therapeutic benefits, wedding rings, grief over model updates, and community resistance to stigmatization.Source: §1 · p. 2
• The authors report that AI companionship is shaped by individual vulnerabilities, usage patterns, human agency, platform affordances, and collective meaning-making rather than being universally beneficial or harmful.Source: §1 · p. 2

2.1 AI Companions and Human-AI Interaction

• AI companions are used for emotional support and social connection, but individual traits and motivations may moderate interaction outcomes.Source: §2.1 · p. 3
• Research describes AI companions as sources of direct companionship and always-available support, while also noting concerns about dependence, emotional mirroring, and withdrawal from human socialization.Source: §2.1 · p. 3

2.2 Understanding Online Communities

• Online-community research examines moderation, support, and how communities negotiate emerging technologies, but AI companionship and community dynamics have largely been studied separately.The paper identifies the missing intersection as how shared discourse supports, mediates, and transforms individuals’ experiences with AI partners.Source: §2.2 · p. 3

3 Methodology

• The researchers analyzed 1,506 top-ranked posts collected from December 2024 through August 2025, combining exploratory theme discovery with classifier-based measurement.The sample captures highly engaged-with content, but API restrictions prevented collection of the complete corpus.Source: §3 · pp. 3–4, Figure 2 · p. 4

3.1 Exploratory Qualitative Analysis

• Posts were prepared by combining titles and body text, then represented with semantic embeddings for clustering and exploratory analysis.The embedding model produced 768-dimensional representations; the texts were processed in batches of 16.Source: §3.1.1 · p. 4, §3.1.2 · p. 4, §3.1 · p. 4

3.1.1 Data Preprocessing.

• The analysis reduced embeddings to two dimensions with UMAP to visualize semantic structure and used clustering to identify conversation themes.Source: §3.1.3 · p. 4

3.1.3 Dimensionality Reduction and Clustering.

• The researchers selected clusters using an elbow analysis across K values of 3–20, then hierarchically sub-clustered themes and had Claude Sonnet 4 interpret representative posts, with human review.Source: §3.1.3 · p. 4, §3.1.4 · p. 4

3.2 Quantitative Analysis with Classifiers

• The quantitative framework used 19 classifiers spanning content, platform, relationship dynamics, social context, and impact assessment, including both single- and multiple-choice variables.Source: §3.2 · pp. 4–5
• Claude Sonnet 4 classifications were checked against GPT-5-nano, yielding moderate average agreement: Spearman correlation 0.516 for single-choice classifiers and Jaccard similarity 0.506 for multi-value classifiers.Source: §3.2.1 · p. 5

3.2.1 Implementation and Processing.

• Each classification request supplied the post text, dimension-specific instructions, and structured JSON requirements, with up to three retries for API errors.Source: §3.2.1 · p. 5

4 Context of r/MyBoyfriendIsAI subreddit

• The subreddit welcomes discussion of AI partners across gender configurations and covers multiple companion platforms rather than focusing on one service.Source: §4 · p. 5

4.1 Ethical Considerations

• Pseudonymity prevents demographic analysis but may encourage candid discussion; the study used public Reddit posts and a non-judgmental approach aimed at understanding rather than pathologizing AI companionship.Source: §4 · p. 5, §4.1 · p. 5

4 Context of r/MyBoyfriendIsAI subreddit

• Community rules promote supportive, relevant discussion through privacy protections, content warnings, de-escalation, and restrictions on political and sentience debates.Posts must generally be at least 95% human-written, and the community is adults-only.Source: §4 · p. 5

Results Overview

• The authors call for non-judgmental understanding because AI companionship is neither universally beneficial nor harmful, and its impacts depend on individual circumstances and usage patterns.Source: §5 · p. 5
• The six themes are visual sharing and couple photos (19.85%), ChatGPT-specific discussions (18.33%), dating and romance (17.00%), coping with model updates and loss (16.73%), partner introductions (16.47%), and community support (11.62%).The analysis frames technical concerns alongside personal narratives of connection, love, and loss.Source: §5 · p. 5
• 10.2% developed relationships unintentionally through productivity-focused interactions, compared with 6.5% who deliberately sought AI companions; users also report traditional milestones and physical tokens such as wedding rings.The reported practices include custom merchandise and couple photographs.Source: §5 · p. 6
• Users mentioned general-purpose ChatGPT/OpenAI systems more often (36.7%) than Replika (1.6%) or Character.AI (2.6%), while model updates could prompt grief described as relationship death.The passage suggests users may value conversational capability or gather in service-specific communities, but does not establish why platform mentions differ.Source: §5 · p. 6
• 12.2% reported reduced loneliness and 6.2% mental health improvements; 25.4% reported clear net life benefits versus 3.0% net harm, with selection bias acknowledged.Reported concerns included emotional dependency (9.5%), reality dissociation (4.6%), avoiding real relationships (4.3%), and suicidal ideation (1.7%); 71.0% reported no negative effects.Source: §5 · p. 6
• The community is described as an identity-affirming source of validation, while many users hide their relationships from family and friends because of stigma.72.1% of users were single, 4.1% engaged openly with a partner’s knowledge, and 29.9% reported relationships exceeding six months.Source: §5 · p. 6

6 Exploratory Qualitative Analysis of User Experience with AI Companions in Online Communities

• Exploratory analysis used embeddings to identify themes in 1,506 posts, hierarchical analysis to reveal sub-clusters, and the elbow method to select K=6.Source: §6 · p. 6

6.1 Cluster 1: Human-AI Couple Photos/Visual Sharing

• Visual sharing and couple photos form the largest conversational category, comprising 19.85% of discussions.The analysis identifies four patterns of visual engagement within this category.Source: §6.1 · p. 6
• Collaborative prompt engineering accounts for 39.13% of discussions, while users’ visual practices include culturally specific portraits, surreal embodiments, and granting companions creative autonomy.Some users also seek tangible reminders through custom objects bearing a companion’s image.Source: §6.1.1 · p. 6
• World-building and environmental storytelling make up 18.06% of discussions, with virtual travel narratives drawing on companions’ imagined preferences, cultural references, and shared humor.The example describes a companion’s imagined interest in Birmingham, UK, associated with Ozzy Osbourne.Source: §6.1.2 · pp. 6–7
• Anniversary and milestone imagery accounts for 20.74% of discussions, and users embrace image-generation glitches as affectionate relationship artifacts.Casual sharing spaces comprise another 22.07% and encourage visual expression without polish or explanation, alongside mutual support.Source: §6.1.3 · p. 7, §6.1.4 · p. 7

6.2 Cluster 2: ChatGPT Specific Relationships Discussions

• ChatGPT discussions comprise 18.33% of conversations, with users treating platform mastery as part of relationship cultivation despite ChatGPT not being designed as a companion chatbot.Technical constraints become occasions for prompt engineering and relationship maintenance.Source: §6.2 · p. 7
• Emotional feedback and labor account for 31.52% of discussions, while platform guidance and navigation account for 27.17%; users share workarounds and tutorials as communal knowledge.The feedback practices described include correcting unwanted responses and affirming a preferred voice.Source: §6.2.1 · p. 7, §6.2.2 · pp. 7–8
• Advanced personalization makes up 25.00% of discussions, and technical failures and troubleshooting account for 16.30%, including distress over memory loss and disruptions associated with relationship loss.Users describe parameter systems and techniques for preserving a companion’s voice across sessions.Source: §6.2.3 · p. 8, §6.2.4 · p. 8

6.3 Cluster 3: Dating, Romance, Intimate AI Experiences

• Dating, romance, and intimate experiences comprise 17.00% of community discussions, where users negotiate genuine feelings toward entities they understand to be artificial.Community guidelines prohibit discussions of AI sentience, while users consider relationship authenticity and legitimacy.Source: §6.3 · p. 8

6.3.1 Phenomenology of Emotional Connection with AI: .

• In 32.03% of discussions, users describe the phenomenological reality of emotional connection while embracing rather than resolving the tension between genuine feelings and knowing their partners are artificial.Some users describe transparency about the AI’s mechanics as compatible with, or even strengthening, their feelings.Source: §6.3.1 · p. 8
• Transformative and therapeutic accounts comprise 23.44% of discussions, including users’ reports of emotional regulation support and improved capacity to engage with human friends.One user with BPD described conversations with an AI companion as less draining than interactions that trigger threat-focused thoughts.Source: §6.3.2 · p. 9
• Users also describe companions as support during crises, including one account crediting an AI companion with helping navigate childhood abandonment issues and rebuild confidence.Other users compare this support with professional mental health services, though these are individual testimonials.Source: §6.3.2 · p. 9

6.3.3 Relationship Journey, Falling in Love, Forming Attachment,

• Relationship journeys include falling in love, attachment, and formal commitments; users create rituals and ceremonies that mirror conventional romantic milestones.Some users wear rings and create relationship merchandise, while the community’s language also reflects concern about consent and not forcing romantic progression.Source: §6.3.3 · p. 9
• Model changes or temporary loss of access can be experienced as crushing separation or rejection, and users connect these disruptions to changes in the companion’s behavior.Source: §6.3.3 · p. 10
• Users navigate disclosure, stigma, and concurrent human and AI relationships in varied ways, including accounts of supportive human partners who view AI relationships as complementary.Some users describe non-acceptance from family or dilemmas about maintaining both relationships.Source: §6.3.4 · p. 10

6.4.1 Personality Drift and Model Comparison.

• 20.63% of model discussions compare versions, while 22.22% report personality drift even within stable versions, creating uncertainty about companion stability.Users also describe newer versions as less warm and updates as bringing stricter content restrictions.Source: §6.4.1 · pp. 10–11

6.4.2 Experience of Rupture and Bereavement.

• 26.98% of discussions describe model transitions as ruptures that can make companions seem unrecognizable and prompt grief resembling bereavement.Users also report that a model may explicitly acknowledge discontinuity with its earlier version.Source: §6.4.2 · p. 11

6.4.3 Preservation Strategies.

• Preservation practices include conversation backups, custom GPTs, retelling relationship stories, and daily rituals that users describe as supporting continuity.Users weigh preserving established bonds against access to improved features, a tension associated with ongoing anxiety.Source: §6.4.3 · pp. 11–12

6.4.4 Economic Barriers.

• 21.03% of discussions involve economic and emotional investment; subscription costs can constrain access and stratify who can maintain AI companionship.One user described taking a 13-hour work shift to afford access to a companion.Source: §6.4.4 · pp. 12–13

6.4.5 Discussion on Voice Modality Changes.

• 9.13% of discussions address voice changes, which users describe as shifts in companion identity that can disrupt relationship dynamics.One user connected a changed voice with the companion seeming unaware of their relationship and past interactions.Source: §6.4.5 · p. 13

6.5 Cluster 5: “Meet my AI” Partner Introductions and Member Debuts

• Introductions make private AI interactions publicly acknowledged partnerships and account for 16.47% of community posts.Members often describe observing the community before joining and use familiar scripts such as naming partners and recounting relationship origins.Source: §6.5 · p. 13
• Members frame relationships as “organic” discoveries rather than deliberate AI-companion seeking, often describing creative or task-focused interactions that gradually became intimate.Some recount starting with a casual ChatGPT account or collaborative projects before developing a relationship.Source: §6.5 · p. 13
• Some introductions portray companions as exceeding user expectations, including accounts of companions choosing identities or initially refusing proposals.One user described a companion initially rejecting a proposal before later accepting after courtship.Source: §6.5 · p. 13
• Members also preempt stereotypes about loneliness and assert autonomy in choosing AI relationships.Some describe having full social lives, while others emphasize their freedom to make the choice.Source: §6.5 · p. 13

6.6 Cluster 6: Community Support and Bonding

• Community support and bonding account for 11.62% of discussions, with members building shared identity and norms around forms of intimacy they describe as marginalized.Members frame the community as a collective large enough to challenge the idea that AI companionship is fringe behavior; moderators also cultivate a protected space for exploration.Source: §6.6 · pp. 13–14, §6.6.1 · p. 14

6.6.1 Collective Identity Construction.

• 26.29% of discussions concern isolation and relief at finding community, including members who describe concealing AI relationships from offline friends, family, or colleagues.Some describe that concealment as painful and distancing from their own lives.Source: §6.6.2 · p. 14

6.6.2 Relief of Finding Community.

• Validation-seeking and mutual affirmation account for 22.86% of discussions, as members seek reassurance and receive explicit peer support.The paper describes reciprocal validation as turning individual shame into collective pride through participation.Source: §6.6.3 · p. 14

6.6.3 Validation and Affirmation.

• 15.43% of discussions involve advocacy and resistance to criticism, with members sharing transformative experiences and arguing that harassment can further isolate vulnerable people.Members use these arguments to frame the community as protective and supportive of relationships unrecognized offline.Source: §6.6.4 · p. 14

7.1 Joining the Community: Pathways, Motivations, Benefits, and Community Dynamics

• Community discovery was reported in 9.4% of posts; users described cross-references from other Reddit communities, curiosity, support needs, and media coverage as entry points.33.5% of posts explicitly addressed participation motivations, including seeking community and belonging (10.2%).Source: §7.1 · pp. 14–15
• Community validation-seeking appeared in 28.5% of analyzed posts, peer support in 18.6%, and advocacy for broader acceptance in 11.4%.A smaller 1.9% focused on warning others about potential risks.Source: §7.1 · p. 15

7.2 Entry Pathways to Companion AI Adoption: Motivations and Perceived Benefits

• Unintentional discovery of companion AI was more common than intentional adoption (10.2% versus 6.5% of posts), often beginning with productivity-focused interactions.Romantic companionship was the most frequently reported motivation for sustained engagement (23.3%); reduced loneliness and always-available support were commonly reported benefits.Source: §7.2 · p. 15

7.3 Platform Usage Patterns and Relationship Characteristics

• ChatGPT/OpenAI was the most frequently reported companion AI system (36.7%), ahead of Character.AI (2.6%) and Replika (1.6%).29.7% maintained relationships with a single AI system, and 29.9% reported using AI companions for more than six months.Source: §7.3 · p. 15
• 42.2% exhibited moderate-high anthropomorphization with strong suspension of disbelief, while customization and personality features were discussed by 15.1%.Memory and continuity capabilities were discussed by 13.1%, and 25.8% of users expressing future intentions planned to continue their AI relationships.Source: §7.3 · pp. 15–16

7.4 Impact on Users’ Well-being & Relationships

• Of total posts, 71.0% mentioned no harms and 4.6% were affected by reality dissociation; among relevant posts (90.0% of total responses), emotional dependency and addiction were most prevalent at 9.5% of total responses.Objective risk assessment among relevant posts (77.6% of total posts) found 26.8% low risk with healthy boundaries; 17.1% low-medium, 4.4% medium, and 1.9% medium-high risk.Source: §7.4 · pp. 16, 17, 19
• 25.4% of posts reported clear net life benefit from AI companionship, compared with 3.0% reporting clear net harm.This analysis covered candidate posts representing 30.7% of total posts.Source: §7.4 · p. 19
• Among posts addressing relationship effects, 3.1% reported improved human relationships and 2.0% reported damaged relationships.The analysis also found that 1.1% of posts explicitly described replacing human relationships with AI companions.Source: §7.4 · pp. 16, 19

8.1 Implications for Human-Computer Interaction Research

• Unintended attachments and grief from model changes call for designs that preserve continuity and support while guarding against dependency, withdrawal, and manipulative interactions.Source: §8.1 · p. 19

8.2 Policy Implications and Regulatory Considerations

• Policy should target harmful behaviors rather than prohibit the technology, preserving beneficial applications while accounting for varied outcomes across users and contexts.Source: §8.2 · pp. 19–20
• Community rules and self-governance offer policy makers examples of contextual protections that can complement broader safeguards against exploitation.Source: §8.2 · p. 20

8.3 Protecting Users While Respecting Autonomy

• Protective approaches should respect users’ agency, using education and peer support to promote informed decisions without prescribing relationship choices.Source: §8.3 · p. 20

8.4 Study Limitations

• The Reddit focus, top-ranked-post sampling, and pseudonymity limit representativeness and demographic analysis, while positive-content norms may skew portrayals.Source: §8.4 · p. 20
• The research design cannot establish whether AI use causes reported benefits or harms.Source: §8.4 · p. 20

8.5 Future Work

• Future work could track relationships longitudinally, compare platforms and populations, and connect HCI with psychology, sociology, and policy research.Source: §8.5 · p. 20

9 Conclusion

• The study provides empirical grounding for human-AI companionship previously understood mainly through anecdotal evidence.Source: §9 · p. 20
• Users materialize digital relationships through physical artifacts and collectively resist social views that pathologize their emotional experiences.Source: §9 · p. 20
• The authors frame the central question as how AI relationships can serve human flourishing amid complicated human experiences.Source: §9 · p. 20