As a primary channel for sustaining modern intimate relationships, instant messaging facilitates frequent connection across distances. However, today's tools often dilute care; they favor single tap reactions and vague emojis that do not support two way action responses, do not preserve the feeling that the exchange keeps going without breaking, and are weakly tied to who we are and what we share. To address this challenge, we present PuppetChat, a dyadic messaging prototype that restores this expressive depth through embodied interaction. PuppetChat uses a reciprocity aware recommender to encourage responsive actions and generates personalized micronarratives from user stories to ground interactions in personal history. Our 10-day field study with 11 dyads of close partners or friends revealed that this approach enhanced social presence, supported more expressive self disclosure, and sustained continuity and shared memories.

翻译：作为维系现代亲密关系的主要渠道，即时通讯促进了远距离间的频繁联系。然而，当前的工具往往弱化了关怀表达：它们倾向于支持单次点击式反应和模糊的表情符号，这些方式既不支持双向行为回应，也无法维持交流持续不断的感觉，且与我们的身份特质及共享内容关联薄弱。为应对这一挑战，我们提出了PuppetChat——一个通过具身交互恢复表达深度的二元消息传递原型。PuppetChat采用具备互惠感知能力的推荐系统来鼓励响应性行为，并从用户故事中生成个性化的微叙事，使互动植根于个人历史之中。我们通过对11组亲密伴侣或朋友开展的10天实地研究表明，该方法显著增强了社交临场感，支持更具表达性的自我表露，并有效维系了交流的连续性与共同记忆。