mlsanityData to 14 Oct 2026

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

arXiv 2505.20464 ↗First posted 26 May 2025cs.HC cs.CLcited by 6

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 13 of its 109 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

13 of 109 references.

References · 13

  1. 2020Extracting Training Data from Large Language Modelscited by 2,189
  2. 2022What Does it Mean for a Language Model to Preserve Privacy?cited by 195
  3. 2023"It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agentscited by 60
  4. 2020Conceptual Metaphors Impact Perceptions of Human-AI Collaborationcited by 47
  5. 2023ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Eventscited by 31
  6. 2025Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agentscited by 26
  7. 2024ComPeer: A Generative Conversational Agent for Proactive Peer Supportcited by 24
  8. 2025Chatbots for Data Collection in Surveys: A Comparison of Four Theory-Based Interview Probescited by 9
  9. 2023Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptionscited by 8
  10. 2025Users' Mental Models of Generative AI Chatbot Ecosystemscited by 7
  11. 2020Submitting surveys via a conversational interface: an evaluation of user acceptance and approach effectivenesscited by 6
  12. 2025AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Trackingcited by 4
1 more
  1. 2023What Types of Questions Require Conversation to Answer? A Case Study of AskReddit Questionscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.