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Correlating msm's mental health with usage behaviors on msm-specific social applications

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Published
Publication date23/08/2019
Number of pages8
Pages891-898
<mark>Original language</mark>English
Event2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBD) - Leicester, UK , Leicester , United Kingdom
Duration: 19/08/2019 → 23/08/2019
https://www.aconf.org/conf_173124.html

Conference

Conference2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBD)
Abbreviated titleIEE SmartWorld '19
Country/TerritoryUnited Kingdom
CityLeicester
Period19/08/19 → 23/08/19
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Abstract

Homophobia and discrimination towards men who have sex with men (MSM) make the mental health of this community a severe concern. The prevalence of mobile social apps for MSM provides a new channel to study their mental health issues. However, the correlation between the psychological states of MSM and their behaviors on social apps are still uninvestigated. In this paper, we conduct a case study of 103 MSM in China to explore whether the User Generated Content, Profile, Mobility information of MSM on social apps correlate with their depression, loneliness, anxiety and stress level. The analysis results indicate that the mental health disorder level of MSM is correlated with the emotion expressed in posts, whether the user has filled in self-description blank, the social relationship among online friends, frequency of visiting popular gays-meeting places. Our findings imply future opportunities in early psychological problems detection and intervention. © 2019 IEEE.

Bibliographic note

Export Date: 29 April 2020 Correspondence Address: Wang, J.; School of Computing and Communications, Lancaster UniversityUnited Kingdom; email: wangyasha@pku.edu.cn Funding details: Science and Technology Major Project of Guangxi, 2018ZX10201002 Funding details: National Natural Science Foundation of China, NSFC, 61772045 Funding text 1: This work is supported by the National Science and Technology Major Project (No. 2018ZX10201002) and the National Natural Science Foundation of China (No.61772045).