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

TL;DR

Remini is a chatbot that facilitates mutual reminiscence between loved ones, significantly enhancing positive emotions, connection, and detailed shared narratives through structured, emotionally rich dialogue guided by AI.

Contribution

This paper introduces Remini, a novel chatbot framework that supports reciprocal self-disclosure for mutual reminiscence, grounded in the SFAM framework, with empirical validation showing improved emotional and relational outcomes.

Findings

Remini significantly increased positive affect and feelings of connectedness.

Participants engaged in more detailed and reciprocal storytelling with Remini.

Structured AI guidance improved emotional and relational benefits of reminiscence.

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.