Facebook language predicts depression in medical records

@article{Eichstaedt2018FacebookLP,
  title={Facebook language predicts depression in medical records},
  author={Johannes C. Eichstaedt and Robert J. Smith and Raina M. Merchant and Lyle H. Ungar and Patrick Crutchley and Daniel Preotiuc-Pietro and David A. Asch and H. A. Schwartz},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  year={2018},
  volume={115},
  pages={11203 - 11208}
}
Significance Depression is disabling and treatable, but underdiagnosed. In this study, we show that the content shared by consenting users on Facebook can predict a future occurrence of depression in their medical records. Language predictive of depression includes references to typical symptoms, including sadness, loneliness, hostility, rumination, and increased self-reference. This study suggests that an analysis of social media data could be used to screen consenting individuals for… 

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