<scp>Remini:</scp> Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones

Mutual reminiscence, defined as revisiting shared positive memories through reciprocal self-disclosure, strengthens emotional bonds, enhances well-being, and deepens intimacy. However, most technology-mediated reminiscence tools emphasize individual reflection or one-way storytelling, which overlooks the dynamic, interactive dialogue essential for meaningful mutual reminiscence. To address this limitation, we introduce Remini, a chatbot designed to support reciprocal self-disclosure between close partners such as couples, friends, or family members. Grounded in the Social Functions of Autobiographical Memory (SFAM) framework, Remini uses conversational AI to guide emotionally rich exchanges through five narrative phases: rapport building, memory narration, elaboration, reflection, and summary. In a mixed-method, both between- and within- subjects study (N = 48, 24 dyads), we compare Remini to a baseline chatbot that offers minimal memory-trigger prompts. Our findings show that structured guidance from Remini significantly improves positive affect, feeling of connection, and engagement. It also fosters more detailed narrative co-construction and greater reciprocal self-disclosure. Participant feedback highlights the practical value, perceived benefits, and design considerations of chatbot-mediated reminiscence. We contribute empirically grounded design implications for conversational agents that strengthen human connection through mutual reminiscence.

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Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757650
Primary Topic
Identity, Memory, and Therapy
Type
article
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article

Remini: Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones

Simon T. Perrault, ShunYi Yeo, Zhuoqun Jiang, Donovan Seow Wei Xuan
Proceedings of the ACM on Human-Computer Interaction
Identity, Memory, and Therapy
article

Remini: Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones

Simon T. Perrault, ShunYi Yeo, Zhuoqun Jiang, Donovan Seow Wei Xuan
article en

Abstract

Mutual reminiscence, defined as revisiting shared positive memories through reciprocal self-disclosure, strengthens emotional bonds, enhances well-being, and deepens intimacy. However, most technology-mediated reminiscence tools emphasize individual reflection or one-way storytelling, which overlooks the dynamic, interactive dialogue essential for meaningful mutual reminiscence. To address this limitation, we introduce Remini, a chatbot designed to support reciprocal self-disclosure between close partners such as couples, friends, or family members. Grounded in the Social Functions of Autobiographical Memory (SFAM) framework, Remini uses conversational AI to guide emotionally rich exchanges through five narrative phases: rapport building, memory narration, elaboration, reflection, and summary. In a mixed-method, both between- and within- subjects study (N = 48, 24 dyads), we compare Remini to a baseline chatbot that offers minimal memory-trigger prompts. Our findings show that structured guidance from Remini significantly improves positive affect, feeling of connection, and engagement. It also fosters more detailed narrative co-construction and greater reciprocal self-disclosure. Participant feedback highlights the practical value, perceived benefits, and design considerations of chatbot-mediated reminiscence. We contribute empirically grounded design implications for conversational agents that strengthen human connection through mutual reminiscence.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Singapore University of Technology and Design (SG)
Openalex Percentile: Top 69%
Identity, Memory, and Therapy
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<scp>Remini:</scp> Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones — Simon T. Perrault, ShunYi Yeo, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS