Reconstruction and Reflection of Positive Experiences through Resurfacing Laughter-indexed Everyday Moments

2026-09-11

AI Summary

研究通过检测笑声来索引日常生活中的积极时刻，利用LaughAnchor系统帮助用户记录、回顾和反思这些时刻，从而支持正面经历的重构与反思。

Abstract

Positive everyday moments often escape deliberate recording, while continuous self-tracking can generate extensive records that are difficult to revisit. We explore laughter as a naturally occurring, sparse index for constructing contextualized personal records to support later reconstruction and reflection. A formative study with 12 participants characterized laughter as an affective but semantically incomplete index and informed \textit{LaughAnchor}, a mobile and wearable self-tracking system. During participant-initiated recording, the system assembles detected laughter and aligned context into candidate moments for later reconstruction and reflection, with layered context disclosure, user-controlled curation, and near-term and long-term resurfacing. In a three-week field deployment with 12 participants, passive indexing preserved moments they considered unlikely to record deliberately but valued retrospectively. During resurfacing, participants attributed affective re-experiencing to laughter and used additional context both to reconstruct episodes and to explore already-recalled experiences. Across moments and reviews, resurfacing supported rediscovery and broader awareness of relationships, routines, and emotional states. These findings inform self-tracking designs that use sparse affective indices to organize contextual records for reconstruction and reflection, while keeping interpretation and retention under user control.

Problem

• laughter
• self-tracking
• positive experiences
• contextualized records
• reconstruction and reflection

Innovation

• laughter-indexed moments
• contextualized personal records
• self-tracking system
• affective re-experiencing