Private traits and attributes are predictable from digital records of human behavior.

@article{Kosinski2013PrivateTA,
  title={Private traits and attributes are predictable from digital records of human behavior.},
  author={Michal Kosinski and David Stillwell and Thore Graepel},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  year={2013},
  volume={110 15},
  pages={
          5802-5
        }
}
We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles… CONTINUE READING

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