Remini: Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones
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arXiv
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| Format: | Preprint |
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2025
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| author | Jiang, Zhuoqun Yeo, ShunYi Seow, Wei Xuan Donovan Perrault, Simon |
| author_facet | Jiang, Zhuoqun Yeo, ShunYi Seow, Wei Xuan Donovan Perrault, Simon |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_03355 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Remini: Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones Jiang, Zhuoqun Yeo, ShunYi Seow, Wei Xuan Donovan Perrault, Simon Human-Computer Interaction 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. |
| title | Remini: Leveraging Chatbot-Mediated Mutual Reminiscence for Promoting Positive Affect and Feeling of Connectedness among Loved Ones |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2508.03355 |