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A Scorecard Method for Detecting Depression in Social Media Users

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Title: A Scorecard Method for Detecting Depression in Social Media Users
Authors: Tefera, Netsanet Legesse
Zhou, Lina
Keywords: Technology Mediated Collaborations in Healthcare and Wellness Management
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Issue Date: 03 Jan 2018
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.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/49958
ISBN: 978-0-9981331-1-9
DOI: 10.24251/HICSS.2018.071
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Technology Mediated Collaborations in Healthcare and Wellness Management


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