Affiliation:
1. KAIST, Daejeon, Republic of Korea
2. Carnegie Mellon University, Pittsburgh, PA, USA
3. Hanyang University, Seoul, Republic of Korea
Abstract
Many digital wellbeing tools help users monitor and control social media use on their smartphones by tracking and setting limits on their usage time. Tracking is typically done at the granularity of phone- or app-level; however, recent social media apps provide various features such as direct messaging, comment reading/posting, and content uploading/viewing. While it is possible to track and analyze within-app feature usage, little is known about the effect of granularity on smartphone interventions. We designed and developed FinerMe to explore how the granularity of interventions (app-level vs. feature-level) affects the usage of popular social media such as Instagram and YouTube on smartphones. We conducted a field study with 56 participants over 16 days that consisted of three phases: baseline collection, self-reflection, and self-reflection with restrictive interventions. The results showed that while both app-level and feature-level interventions similarly reduced social media use, feature-level interventions enabled users to spend less time on passive app features related to content consumption (e.g., following feed on Instagram, and viewing comments on YouTube) than app-level interventions. Moreover, when self-reflection is combined with restrictive interventions at the feature-level, users were more reflective on their usage behavior than when done at the app-level.
Funder
Institute of Information & communications Technology Planning & Evaluation
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)
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