articleJan 1, 2014GOLD OA

Quantifying Mental Health Signals in Twitter

Johns Hopkins University

Indexed incrossref

Abstract

The ubiquity of social media provides a rich opportunity to enhance the data available to mental health clinicians and researchers, enabling a better-informed and better-equipped mental health field. We present analysis of mental health phenomena in publicly available Twitter data, demonstrating how rigorous application of simple natural language processing methods can yield insight into specific disorders as well as mental health writ large, along with evidence that as-of-yet undiscovered linguistic signals relevant to mental health exist in social media. We present a novel method for gathering data for a range of mental illnesses quickly and cheaply, then focus on analysis of four in particular:…

Citation impact

702
total citations
FWCI
41.60
Percentile
100%
References
43
Citations per year

Authors

3

Topics & keywords

Keywords
  • Mental health
  • Computer science
  • Social media
  • Psychology
  • World Wide Web
  • Psychiatry
UN Sustainable Development Goals
  • Quality Education
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