Next Article in Journal
Sustainable Working Life in Intensive Care: A Qualitative Study of Older Nurses
Previous Article in Journal
Evolution of Therapeutic Patient Education: A Systematic Scoping Review and Scientometric Analysis
 
 
Article

What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?

School of Management, Shanghai University, Shanghai 201800, China
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2022, 19(10), 6129; https://doi.org/10.3390/ijerph19106129
Received: 19 March 2022 / Revised: 7 May 2022 / Accepted: 10 May 2022 / Published: 18 May 2022
(This article belongs to the Section Digital Health)
Social media platforms provide unique insights into mental health issues, but a large number of related studies have focused on English text information. The purpose of this paper is to identify the posting content and posting behaviors of users with depression on Chinese social media. These clues may suggest signs of depression. We created two data sets consisting of 130 users with diagnosed depression and 320 other users that were randomly selected. By comparing and analyzing the two data sets, we can observe more closely how users reveal their signs of depression on Chinese social platforms. The results show that the distribution of some Chinese speech users with depression is significantly different from that of other users. Emotional sadness, fear and disgust are more common in the depression class. For personal pronouns, negative words and interrogative words, there are also great differences between the two data sets. Using topic modeling, we found that patients mainly discussed seven topics: negative emotion fluctuation, disease treatment and somatic responses, sleep disorders, sense of worthlessness, suicidal extreme behavior, seeking emotional support and interpersonal communication. The depression class post negative polarity posts much more frequently than other users. The frequency and characteristics of posts also reveal certain characteristics, such as sleep problems and reduced self-disclosure. In this study, we used Chinese microblog data to conduct a detailed analysis of the users showing depression signs, which helps to identify more patients with depression. At the same time, the study can provide a further theoretical basis for cross-cultural research of different language groups in the field of psychology. View Full-Text
Keywords: online social media; depression; natural language processing; text analysis online social media; depression; natural language processing; text analysis
Show Figures

Figure 1

MDPI and ACS Style

Liu, J.; Shi, M. What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts? Int. J. Environ. Res. Public Health 2022, 19, 6129. https://doi.org/10.3390/ijerph19106129

AMA Style

Liu J, Shi M. What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts? International Journal of Environmental Research and Public Health. 2022; 19(10):6129. https://doi.org/10.3390/ijerph19106129

Chicago/Turabian Style

Liu, Jingfang, and Mengshi Shi. 2022. "What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?" International Journal of Environmental Research and Public Health 19, no. 10: 6129. https://doi.org/10.3390/ijerph19106129

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop