Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data

Abstract

Existing studies have shown that temperature is related to mental illness and sleep disorders. However, few studies have explored the relationship between temperature and microblog negative emotions (MNE) and the predictive effect of MNE on sleep disorders. The present study elucidating the temperature patterns of MNE and sleep disorders, examines the predictive capability of these adverse emotions in precipitating sleep disorders, and operating within the schema of “climate-psychology-behavior”. A negative binomial regression model (NBR) was formulated, amalgamating Temperature data, negative affective information procured from microblog, and sleep disorder records. Temperature and Apparent Air Temperature (AAT) were found to have a non-linear association with microblog negative emotions and sleep disorders, exhibiting a modest effect within a specified range, while extreme temperatures (both high and low) demonstrated substantial effects. In the constructed model, gender serves as a moderating factor, with females being more susceptible to temperature and AAT effects on MNE and sleep disorders than their male counterparts. Interestingly, AAT surfaced as a superior predictor compared to actual temperature. MNE were effective predictors of sleep disorders. Employing social media-centric models, as showcased in this study, augments the identification and prevention strategies targeting disease symptoms or pathologies within mental and public health domains.