Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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K-Means clustering on 551 survey responses identified 6 groups with distinct patterns linking social media hours to anxiety, depression, loneliness, and sleep quality.
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Before You Scroll Again: Predicting Regretful Social Media Sessions from In-the-Wild Contextual and Wearable Sensing
Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
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Uncovering Latent Patterns in Social Media Usage and Mental Health: A Clustering-Based Approach Using Unsupervised Machine Learning
K-Means clustering on 551 survey responses identified 6 groups with distinct patterns linking social media hours to anxiety, depression, loneliness, and sleep quality.