From Platform Data to Personal Insight: How Users Make Sense of and Reflect on Personalized Social Media Annual Recaps
Wenqi Li, Jinghan Zhang, Junyang Ma, Pengyi Zhang
Abstract
Social media platforms generate personalized annual recaps presenting algorithmically-curated summaries of users’ online activities. Unlike traditional personal informatics where users actively collect data, these recaps present unsolicited insights demanding sensemaking effort. Through interviews with 20 participants and analysis of annual recaps, we investigated how users make sense of and reflect on these presentations. We identified seven data presentation types and five sensemaking activities facilitating different reflection levels. We found that concrete presentations like extreme details serve as foundational anchors across all levels, while more abstract presentations predominantly prompt critical reflection. Sensemaking activities lead to reflection through four paths: descriptive reflection involves scanning and annotation, dialogic reflection requires explanation-seeking activities, transformative reflection involves comprehensive sensemaking processes with emphasis on verification, while critical reflection can emerge from any path. We contribute theoretical bridges between sensemaking and reflection in personal informatics and provide design implications to support sensemaking and reflection on personal data.
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