Negotiating Digital Identities with AI Companions: Motivations, Strategies, and Emotional Outcomes

Paper Title

Negotiating Digital Identities with AI Companions: Motivations, Strategies, and Emotional Outcomes

Publication Info

• Topic area: Identity negotiation and emotional interaction with AI companions.
• Keywords: AI companions, identity negotiation, emotional attachment, Character.AI, human-AI interaction, thematic analysis, socio-emotional sandbox, chatbot personas, emotional regulation, fandom.

Background and Problem

• Problem / challenge: Existing research has explored the psychological impacts and ethical challenges of AI companions but has not sufficiently examined how users present their identities and configure AI characters to meet socio-emotional needs.
• Significance: Understanding identity negotiation with AI companions is critical for mitigating risks like unhealthy emotional dependence and designing safer, emotionally supportive AI systems.
• Motivation and related work: Prior studies have focused on AI companions' psychological benefits (e.g., reducing loneliness) and risks (e.g., emotional dependence). However, the process of identity construction and negotiation with AI companions, particularly in platforms like Character.AI, remains underexplored.

Solution

• Proposed approach: A three-stage identity negotiation framework applied to Character.AI interactions, analyzed through Identity Negotiation Theory (INT).
• Novelty:
  1. Detailed empirical account of identity negotiation on an AI companion platform.
  2. Conceptualization of users as both performers and directors in identity co-construction.
  3. Design implications for safer and emotionally supportive AI companions.
• Procedure and key techniques:
  • Data collection: 22,374 posts from the r/CharacterAI subreddit.
  • LLM-assisted thematic analysis using INT dimensions (motivation, communication, identity, emotion).
  • Identification of user motivations, communication expectations, identity co-construction strategies, and emotional outcomes.

Results

• Concrete findings:
  • Five user motivations: social fulfillment (35.84%), emotional regulation (28.55%), immersive fanwork (20.34%), creative utility (20.28%), and violence play (15.00%).
  • Three communication expectations: conversational context comprehension (61.78%), managed conversational boundaries (28.16%), and trained characterization (17.23%).
  • Four identity co-construction strategies: bot identity alignment (19.36%), direction of chatbot identity (28.07%), user persona enactment (13.94%), and user identity reference (8.29%).
  • Emotional outcomes: emotional attachment (53.00%), bot interaction embarrassment (6.60%), and deceased memory interactions (2.81%).
• Advantage over baselines: Provides a nuanced understanding of identity negotiation processes, extending prior work that focused only on outcomes like emotional support or ethical risks.
• Experiments / evaluation:
  • Data from public Reddit discussions.
  • Thematic analysis validated with Krippendorff’s alpha (e.g., 0.73 for identity, 0.64 for motivation).
  • LLM annotations cross-validated with human coders.
• Limitations and future work:
  • Focused on a single platform (Character.AI) and subreddit community, which may not generalize to other AI companion platforms.
  • LLM-assisted analysis may have inherent biases; future work could expand to other datasets and methods.

Summary

This study investigates identity negotiation in human-AI interactions on Character.AI using Identity Negotiation Theory. It identifies a three-stage process involving user motivations, communication expectations, identity co-construction strategies, and emotional outcomes. Key findings highlight users’ dual roles as performers and directors, the socio-emotional sandbox nature of AI companions, and the risks of emotional attachment and identity misalignment. The study provides actionable design implications for safer, emotionally supportive AI companions, emphasizing user agency and responsible governance.