The Impact of a Chatbot's Ephemerality-Framing on Self-Disclosure Perceptions

2025-05-26

AI Summary

This study investigates how chatbots’ relational framing—“familiar” versus “stranger”—influences users’ self-disclosure willingness and experience. Employing a mixed within- and between-subjects design with a two-day, two-session dialogue paradigm, it integrates quantitative perceptual measures and in-depth interviews. Results reveal the temporal sensitivity of relational framing: the “stranger” condition significantly increases comfort during initial emotional disclosure, whereas the “familiar” condition enhances subsequent interaction enjoyment only after users first establish trust through factual self-disclosure. Qualitative analysis identifies anonymity and perceived intrusiveness as critical perceptual dimensions. Moving beyond static relational assumptions, this work proposes and empirically validates a dynamic adaptation mechanism for human–AI relational framing. It thus provides both theoretical grounding and empirical evidence for designing explainable, controllable conversational agents.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Intelligent User Interfaces
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search

Abstract

Self-disclosure, the sharing of one's thoughts and feelings, is affected by the perceived relationship between individuals. While chatbots are increasingly used for self-disclosure, the impact of a chatbot's framing on users' self-disclosure remains under-explored. We investigated how a chatbot's description of its relationship with users, particularly in terms of ephemerality, affects self-disclosure. Specifically, we compared a Familiar chatbot, presenting itself as a companion remembering past interactions, with a Stranger chatbot, presenting itself as a new, unacquainted entity in each conversation. In a mixed factorial design, participants engaged with either the Familiar or Stranger chatbot in two sessions across two days, with one conversation focusing on Emotional- and another Factual-disclosure. When Emotional-disclosure was sought in the first chatting session, Stranger-condition participants felt more comfortable self-disclosing. However, when Factual-disclosure was sought first, these differences were replaced by more enjoyment among Familiar-condition participants. Qualitative findings showed Stranger afforded anonymity and reduced judgement, whereas Familiar sometimes felt intrusive unless rapport was built via low-risk Factual-disclosure.

Problem

• How chatbot's ephemerality-framing affects self-disclosure perceptions
• Comparing Familiar vs Stranger chatbots' impact on emotional disclosure
• Exploring anonymity and rapport in chatbot-user interactions

Innovation

• Ephemerality-framing affects chatbot self-disclosure
• Familiar vs Stranger chatbot interaction comparison
• Emotional and Factual disclosure sequence impact