Using Depression Analytics to Reduce Stigma via Social Media: BlueFriends

Haimson, Oliver L.; Ringland, Kathryn; Simpson, Simone; Wolf, Christine T.

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https://hdl.handle.net/2142/48827 Copy

Description

Title

Using Depression Analytics to Reduce Stigma via Social Media: BlueFriends

Author(s)

• Haimson, Oliver L.
• Ringland, Kathryn
• Simpson, Simone
• Wolf, Christine T.

Issue Date

2014-04-04

Keyword(s)

• social media
• Facebook
• information visualization
• network visualization
• depression
• stigma
• stigma reduction

Abstract

Stigma associated with depression and mental illness is a widespread problem, often leading to negative health outcomes and discrimination for people with these conditions. Common stigma reduction interventions focus on two strategies: education (increasing basic understanding of the condition) and social contact (humanizing or ‘putting a face’ to the condition). These interventions have been explored in various formats, but little is known about the potential of leveraging online social media outlets to reduce stigma. BlueFriends is an application that seeks to reduce stigma by displaying a shareable information visualization graphic aimed at increasing both education and social contact. This application employs a predictive model of depression detection on Facebook. It visualizes the potential proportion of depression in a user’s online social network and displays a comparison of depression prevalence with other common prevalence levels in the US. BlueFriends expands current stigma reduction interventions by leveraging online social environments. By creating customized visualizations that users can share within their network, we hypothesize that BlueFriends will prompt collective stigma reduction and societal depression awareness.

Publisher

iSchools

Series/Report Name or Number

iConference 2014 (Social Media Expo)

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/48827

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