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Characterizing Depression Issues on Sina Weibo

Author

Listed:
  • Xianyun Tian

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Philip Batterham

    (Centre for Mental Health Research, The Australian National University, Canberra ACT 2601, Australia)

  • Shuang Song

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Xiaoxu Yao

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Guang Yu

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

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.

Suggested Citation

  • Xianyun Tian & Philip Batterham & Shuang Song & Xiaoxu Yao & Guang Yu, 2018. "Characterizing Depression Issues on Sina Weibo," IJERPH, MDPI, vol. 15(4), pages 1-11, April.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:4:p:764-:d:141207
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    References listed on IDEAS

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    1. Xianyun Tian & Fang He & Philip Batterham & Zheng Wang & Guang Yu, 2017. "An Analysis of Anxiety-Related Postings on Sina Weibo," IJERPH, MDPI, vol. 14(7), pages 1-10, July.
    2. Colin D Mathers & Dejan Loncar, 2006. "Projections of Global Mortality and Burden of Disease from 2002 to 2030," PLOS Medicine, Public Library of Science, vol. 3(11), pages 1-20, November.
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    Cited by:

    1. Xuening Wang & Xianyun Tian & Xuwei Pan & Dongxu Wei & Qi Qi, 2021. "What Happens When People with Depression Gather Online?," IJERPH, MDPI, vol. 18(16), pages 1-12, August.
    2. Wenze Lu & Cindy Sing Bik Ngai & Lu Yang, 2020. "The Importance of Genuineness in Public Engagement—An Exploratory Study of Pediatric Communication on Social Media in China," IJERPH, MDPI, vol. 17(19), pages 1-23, September.
    3. Guangyu Hu & Xueyan Han & Huixuan Zhou & Yuanli Liu, 2019. "Public Perception on Healthcare Services: Evidence from Social Media Platforms in China," IJERPH, MDPI, vol. 16(7), pages 1-10, April.
    4. Ruheng Yin & Rui Tian & Jing Wu & Feng Gan, 2022. "Exploring the Factors Associated with Mental Health Attitude in China: A Structural Topic Modeling Approach," IJERPH, MDPI, vol. 19(19), pages 1-15, October.
    5. Kang, Lili & Peng, Fei & Anwar, Sajid, 2022. "All that glitters is not gold: Do movie quality and contents influence box-office revenues in China?," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 492-510.
    6. Syahrir Zaini & Harvin Anbu Manivanna Bharathy & Ahmad Hatim Sulaiman & Jesjeet Singh Gill & Koh Ong Hui & Hasniza Zaman Huri & Siti Hadijah Shamsudin & Ng Chong Guan, 2018. "Development of a Strategic Tool for Shared Decision-Making in the Use of Antidepressants among Patients with Major Depressive Disorder: A Focus Group Study," IJERPH, MDPI, vol. 15(7), pages 1-12, July.
    7. Jingyun Tang & Guang Yu & Xiaoxu Yao, 2020. "A Comparative Study of Online Depression Communities in China," IJERPH, MDPI, vol. 17(14), pages 1-13, July.

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