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Leveraging Social Media to Predict COVID-19–Induced Disruptions to Mental Well-Being Among University Students: Modeling Study

Leveraging Social Media to Predict COVID-19–Induced Disruptions to Mental Well-Being Among University Students: Modeling Study

We referred to the selection of 50 LIWC categories by De Choudhury et al [32] to describe each post in our data set in terms of the occurrence of these 50 psycholinguistic attributes. To extract longitudinal trends in people’s behaviors and attitudes, we sought to assign psycholinguistic attributes temporally. College students use social media quite often, but not all usage involves posting content. Even though our data spanned over 2 years, a large number of days did not have any posts.

Vedant Das Swain, Jingjing Ye, Siva Karthik Ramesh, Abhirup Mondal, Gregory D Abowd, Munmun De Choudhury

JMIR Form Res 2024;8:e52316