Open AccessProceedings Article
Predicting Depression via Social Media
Munmun De Choudhury,Michael Gamon,Scott Counts,Eric Horvitz +3 more
- Vol. 7, Iss: 1, pp 128-137
TLDR
It is found that social media contains useful signals for characterizing the onset of depression in individuals, as measured through decrease in social activity, raised negative affect, highly clustered egonetworks, heightened relational and medicinal concerns, and greater expression of religious involvement.Abstract:
Major depression constitutes a serious challenge in personal and public health. Tens of millions of people each year suffer from depression and only a fraction receives adequate treatment. We explore the potential to use social media to detect and diagnose major depressive disorder in individuals. We first employ crowdsourcing to compile a set of Twitter users who report being diagnosed with clinical depression, based on a standard psychometric instrument. Through their social media postings over a year preceding the onset of depression, we measure behavioral attributes relating to social engagement, emotion, language and linguistic styles, ego network, and mentions of antidepressant medications. We leverage these behavioral cues, to build a statistical classifier that provides estimates of the risk of depression, before the reported onset. We find that social media contains useful signals for characterizing the onset of depression in individuals, as measured through decrease in social activity, raised negative affect, highly clustered egonetworks, heightened relational and medicinal concerns, and greater expression of religious involvement. We believe our findings and methods may be useful in developing tools for identifying the onset of major depression, for use by healthcare agencies; or on behalf of individuals, enabling those suffering from depression to be more proactive about their mental health.read more
Citations
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Can People’s Depression Level Affect How They Respond to Related Information?: Information Relevance as a Mediator
TL;DR: Zhang et al. as discussed by the authors investigated how individuals respond to a Weibo post addressing depression, based on their depression level and perceived relevance of the information contained in the post, and proposed a research model, in which information relevance mediates the relationship between individuals' depression status and their intended behavior of information exchange (i.e., reposting, liking and commenting).
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Depressive Emotion Tendency Detection for Users on Social Platform Based on Fusion of Graph and Text
TL;DR: Compared with the single-feature method, the image-text feature fusion method can effectively detect the depressive emotion tendency of social platform users.
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Loneliness and Social Media Use Among Adolescents with Psychiatric Disorders
Maya Schwartz-Lifshitz,Nimrod Hertz-Palmor,Idit Dekel,Livia Balan-Moshe,Ehud Mekori-Domachevsky,Hana Weisman,Sharon R. Kaufman,Doron Gothelf,Yair Amichai-Hamburger +8 more
TL;DR: It is indicated that both online and offline social capital are associated with loneliness, and the importance of studying the effect of peer online social support in alleviating loneliness is highlighted.
References
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Journal ArticleDOI
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
TL;DR: The CES-D scale as discussed by the authors is a short self-report scale designed to measure depressive symptomatology in the general population, which has been used in household interview surveys and in psychiatric settings.
Journal ArticleDOI
The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R).
Ronald C. Kessler,Patricia A. Berglund,Olga Demler,Robert Jin,Doreen S. Koretz,Kathleen R. Merikangas,A. John Rush,Ellen E. Walters,Philip S. Wang +8 more
TL;DR: Notably, major depressive disorder is a common disorder, widely distributed in the population, and usually associated with substantial symptom severity and role impairment, and while the recent increase in treatment is encouraging, inadequate treatment is a serious concern.