Name Women’s Mental Health and Social Media
Source UN Women
Hyperlink to Source
Description A study in which researches mine social media feeds for indicators of mental disorders.
Long description Social media, in particular Twitter feeds, are increasingly being used for health surveillance purposes. Infectious diseases (especially influenza) are the most commonly studied pathologies. However, applications to study population-wide emotional states are beginning to be developed using psychological tools like the Profile of Mood States, which identifies moods like tension, depression, anger, fatigue, vigor, and confusion. This project envisions developing diagnostic models that could infer the existence of various mental disorders, especially depressive and alcohol use disorders, among girls and young women from social media content. The key challenge will be “training” the model: confirming inferences with reference to clinical medical diagnoses. Some initial work has been done in this area with Facebook posts and alcohol abuse. In addition, in instances when social media users have elected not to disclose their sex, methods to automatically identify latent user attributes will have to be developed; again, some pioneering work exists, although accounting for cultural differences is critical.
Lead Institution UN Women
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Partners Qatar Computing Research Institute (QCRI), Getúlio Vargas Foundation (Brazil)
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Type Knowledge
Potential for reuse Low
Open source No
Open Source URL
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Maintenance Requirements
Plug & Play No
Outputs compatible with indicators from Official Statistics No
Status Concept
Country use cases
Target Groups
Sectors where the innovation can be applied
  • Gender
  • ,
  • Health
  • Areas of technological innovation
  • Social Media Data
  • Areas of management practice innovations
    Use of Alternative Data Sources
    Areas of institutional process innovations
    Case Study URL with Public Sector Participation
    Case Study Description
    Picture describing Case Study
    Good practices displayed
    Created On 2014-04-12
    Updated On 2014-04-12
    Status Published
    Framework
    Build




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