More Depression-Related Public Concern After the Suicide of a Pop Star in China: Evidence From the Online Big Data Platform

Temporal and Spatial Analysis of Negative Emotions in China during the COVID-19 Pandemic

This research aims to explore the spatiotemporal distribution patterns of negative emotions in mainland China during different stages of the COVID-19 pandemic and the external factors influencing this clustering. Using Baidu Index data for 91 negative emotion keywords, a retrospective geographic analysis was conducted across Chinese provinces from 14 October 2019 to 7 July 2022. Four spatial analysis methods (Global Moran's Index, Local Moran's Index, Bivariate Global Moran's Index, and Bivariate Local Moran's Index) are employed to identify potential clustering patterns and influencing factors of negative emotions at different stages. The results indicate that the COVID-19 pandemic significantly intensified the clustering effect of negative emotions in China, particularly with a more pronounced radiation effect in northwestern provinces. Spatial positive correlations are observed between pandemic-related Baidu indices (pandemic Baidu index, government Baidu index, nucleic acid Baidu index) and negative emotions. These findings contribute to understanding the spatiotemporal distribution characteristics of negative emotions in China post the COVID-19 outbreak and can guide the allocation of psychological resources during emergencies, thereby promoting social stability.

Does Mobile Internet Use Affect the Depression of Young Chinese Adults? An Instrumental Variable Quantile Analysis

BACKGROUND

With the advancement of the digital age, the links between mobile Internet use (MIU) and mental health have attracted the attention of scholars. This paper focuses on the relationship between MIU and depression across the entire distribution of young adults' depression.

METHODS

Based on nationally representative data from the 2018 China Family Panel Studies (CFPS), we explore whether and to what extent MIU affects depression in young adults in China through instrumental variables. In addition, we employ a quantile regression approach to explore the depression-MIU gradients and examine potential mediation mechanisms by exploiting variation in several potential intermediates available.

RESULTS

2SLS estimate suggests that MIU is associated with a decrease in young adults' depression by 1.526 points. Besides, the effect of MIU was only significantly negative at the 0.8 to 0.96 quantiles.

DISCUSSIONS

MIU reduces the level of depression in people with higher levels of depression, older age, and who use the Internet for communicative purposes. However, there is no significant gender difference in MIU. In addition, young people will improve their feeling of social comparison when using mobile Internet, thus making them less depressed.

CONCLUSIONS

MIU has a significant positive impact on depression among young Chinese adults.