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Human-Machine Interaction Technology (HIT)

Leveraging Self-Disclosure and Utility Theory for Extracting Different Types of User Information with Conversational Agents

첫 페이지 보기
  • 발행기관
    국제인공지능학회(구 한국인터넷방송통신학회) 바로가기
  • 간행물
    The International Journal of Advanced Smart Convergence 바로가기
  • 통권
    Volume 14 Number 1 (2025.03)바로가기
  • 페이지
    pp.53-65
  • 저자
    Eunseo Yang, Eunyeoul Lee, Yunjung Lee, Xiuyan Zhu, Uran Oh
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A466027

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원문정보

초록

영어
The more precisely an AI system collects and analyzes user information, the more effectively it can tailor future recommendations for each user. However, gathering comprehensive information for individual users remains a significant challenge because they may have concerns about privacy or find the process bothersome. To encourage users to willingly provide diverse and meaningful personal information, we applied two widely discussed concepts in psychology and economics to conversational agents: Self-Disclosure and Utility Theory. Our study revealed that while both conversational strategies influenced user experience, the Utility Theory strategy, when combined with questions targeting opinions and emotions, enhanced users’ willingness to disclose personal information and improved their overall disclosure experience. These results highlight the importance of tailoring conversational strategies to information types to encourage self-disclosure effectively. Based on these findings, we propose design considerations for efficiently gathering user information through conversation.

목차

Abstract
1. Introduction
2. Related Work
2.1 Self-Disclosure in Chatbot Design
2.2 Utility Theory to Encourage User Engagement
3. Method
3.1 Conditions
3.2 Participants
3.3 Experimental Setup
3.4 Procedure
4. Findings
4.1 Highest Privacy Concern with Fact Information
4.2 Disclosure Discomfort with Fact Information and Self-Disclosure Strategy
4.3 Limited Impact of Strategies and Information Types on Intimacy
4.4 Enhanced Perceived Usefulness Achieved through Utility Theory Strategy
4.5 Highlighting Usefulness to Increase Willingness to Share More Information
5. Discussion
5.1 Utilizing Emotions and Opinions than Facts
5.2 Reconsidering Self-Disclosure in Sensitive Contexts
5.3 Considerations for Applying Utility Theory
6. Limitations & Future Works
7. Conclusion
Acknowledgement
References

키워드

User information disclosure Conversational agents Chatbots Interaction design Self- disclosure Utility Theory Interviews Survey

저자

  • Eunseo Yang [ M.A. Program, Department of Artificial Intelligence and Software, Ewha Womans University, Korea ]
  • Eunyeoul Lee [ M.A. Program, Department of Artificial Intelligence and Software, Ewha Womans University, Korea ]
  • Yunjung Lee [ PhD Program, Department of Computer Science and Engineering, Ewha Womans University, Korea ]
  • Xiuyan Zhu [ PhD program, Department of Artificial Intelligence and Software, Ewha Womans University, Korea ]
  • Uran Oh [ Associate Professor, Department of Computer Science and Engineering, Ewha Womans University, Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    국제인공지능학회(구 한국인터넷방송통신학회) [The International Association for Artificial Intelligence]
  • 설립연도
    2000
  • 분야
    공학>전자/정보통신공학
  • 소개
    인터넷방송, 인터넷 TV , 방송 통신 네트워크 및 관련 분야에 대한 국내는 물론 국제적인 학술, 기술의 진흥발전에 공헌하고 지식 정보화 사회에 기여하고자 한다.

간행물

  • 간행물명
    The International Journal of Advanced Smart Convergence
  • 간기
    계간
  • pISSN
    2288-2847
  • eISSN
    2288-2855
  • 수록기간
    2012~2025
  • 십진분류
    KDC 326 DDC 380

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