A Scorecard Method for Detecting Depression in Social Media Users

dc.contributor.author Tefera, Netsanet Legesse
dc.contributor.author Zhou, Lina
dc.date.accessioned 2017-12-28T00:37:58Z
dc.date.available 2017-12-28T00:37:58Z
dc.date.issued 2018-01-03
dc.description.abstract A Scorecard Method for Detecting Depression in Social Media Users Netsanet Tefera Lina Zhou University of Maryland, Baltimore County {netsa2, zhoul}@umbc.edu Abstract Depression is one of the most prevalent mental health disorders today. Depression has become the leading causes of disability and premature mortality partly due to a lack of effective methods for early detection. This research explores how social media can be used as a tool to detect the level of depression in its users by proposing a scorecard method based on their user profiles. In the proposed method, depression is measured by a selected set of key dimensions along with their specific indicators, which are weighted based on their importance for signaling depression in the literature. To evaluate the scorecard method, we compared three types of social media users: users who committed suicide due to depression, users who were likely suffering from depression, and users who were unlikely suffering from depression. The empirical results demonstrate the effectiveness of the scorecard method in detecting depression.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2018.071
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/49958
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Technology Mediated Collaborations in Healthcare and Wellness Management
dc.subject 0
dc.title A Scorecard Method for Detecting Depression in Social Media Users
dc.type Conference Paper
dc.type.dcmi Text
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