FinerMe

Examining App-level and Feature-level Interventions to Regulate Mobile Social Media Use



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 the 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, 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.


Publications


FinerMe: Examining App-level and Feature-level Interventions to Regulate Mobile Social Media Use
Adiba Orzikulova, Hyunsung Cho, Hye-Young Chung, Hwajung Hong, Uichin Lee, and Sung-Ju Lee
ACM Conference On Computer-Supported Cooperative Work And Social Computing (ACM CSCW) 2023.
PDF Blog Post


People


Adiba Orzikulova

KAIST

Hyunsung Cho

Carnegie Mellon University

Hye-Young Chung

Hanyang University

Hwajung Hong

KAIST

Uichin Lee

KAIST

Sung-Ju Lee

KAIST