Work

Social structure and depression in TrevorSpace

Year: 2014

Type: conference-paper

Abstract: We discover patterns related to depression in the social graph of an online community of approximately 20,000 lesbian, gay, and bisexual, transgender, and questioning youth. With survey data on fewer than two hundred community members and the network graph of the entire community (which is completely anonymous except for the survey responses), we detected statistically significant correlations between a number of graph properties and those TrevorSpace users showing a higher likelihood of depression, according to the Patient Healthcare Questionnaire-9, a standard instrument for estimating depression. Our results suggest that those who are less depressed are more deeply integrated into the social fabric of TrevorSpace than those who are more depressed. Our techniques may apply to other hard-to-reach online communities, like gay men on Facebook, where obtaining detailed information about individuals is difficult or expensive, but obtaining the social graph is not.

Source: ACM Conference on Computer Supported Cooperative Work (CSCW)

DOI: 10.1145/2531602.2531704

Authors: Christopher M. Homan, Naiji Lu, Xin Tu, Megan C. Lytle, Vincent M.B. Silenzio

Institutions: Rochester Institute of Technology, University of Rochester

Language: English

Topic: Mental Health via Writing

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, National Institute of Mental Health