the digital footprint

Very interesting new article published about interpreting private traits from online behavior entitlted: Private traits and attributes are predictable from digital records of human behavior by Michal Kosinskia,1, David Stillwella, and Thore Graepel. Here’s the abstract: 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 orienta- tion, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental sepa- ration, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychomet- ric tests. The proposed model uses dimensionality reduction for…
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