ArticleInternational journal of environmental research and public health2018
Characterizing Depression Issues on Sina Weibo.
Article in International journal of environmental research and public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Multidimensional analysis of childbirth experiences on Chinese social media: an integrated approach using LDA, sentiment analysis and deep learning.Frontiers in public health · 2026Article
- Navigating online emotion: affective patterns and depressive traits in youth digital engagement.Frontiers in psychology · 2025Article
- Exploring self-presentation posts of people with depression: themes, stigma, and identity construction.Frontiers in public health · 2025Article
- MHA: a multimodal hierarchical attention model for depression detection in social media.Health information science and systems · 2023Article
- Investigating COVID-19's Impact on Mental Health: Trend and Thematic Analysis of Reddit Users' Discourse.Journal of medical Internet research · 2023Article
- Detecting depression of Chinese microblog usersFrontiers in psychiatry · 2023Article
- Exploring the Factors Associated with Mental Health Attitude in China: A Structural Topic Modeling Approach.International journal of environmental research and public health · 2022Article
- Characteristics of High Suicide Risk Messages From Users of a Social Network-Sina Weibo "Tree Hole".Frontiers in psychiatry · 2022Article
- Portrayals of 2v, 4v and 9vHPV vaccines on Chinese social media: a content analysis of hot posts on Sina Weibo.Human vaccines & immunotherapeutics · 2021Article
- What Happens When People with Depression Gather Online?International journal of environmental research and public health · 2021Article
- The Importance of Genuineness in Public Engagement-An Exploratory Study of Pediatric Communication on Social Media in China.International journal of environmental research and public health · 2020Article
- A Comparative Study of Online Depression Communities in China.International journal of environmental research and public health · 2020Article
- Inspecting Vulnerability to Depression From Social Media Affect.Frontiers in psychiatry · 2020Article
- Public Perception on Healthcare Services: Evidence from Social Media Platforms in China.International journal of environmental research and public health · 2019Article
- Development of a Strategic Tool for Shared Decision-Making in the Use of Antidepressants among Patients with Major Depressive Disorder: A Focus Group Study.International journal of environmental research and public health · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prevalence of depression has increased significantly over the past few years both in developed and developing countries. However, many people with symptoms of depression still remain untreated or undiagnosed. Social media may be a tool to help researchers and clinicians to identify and support individuals who experience depression. More than 394,000,000 postings were collected from China's most popular social media website, Sina Weibo. 1000 randomly selected depression-related postings was coded and analyzed to learn the themes of these postings, and a text classifier was built to identify the postings indicating depression. The identified depressed users were compared with the general population on demographic characteristics, diurnal patterns, and patterns of emoticon usage. We found that disclosure of depression was the most popular theme; depression displayers were more engaged with social media compared to non-depression displayers, the depression postings showed geographical variations, depression displayers tended to be active during periods of leisure and sleep, and depression displayers used negative emoticons more frequently than non-depression displayers. This study offers a broad picture of depression references on China's social media, which may be cost effectively developed to detect and help individuals who may suffer from depression disorders.
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