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Karen is a life coach and she's happy to help you work through a few things in your life. You interact with Karen through an app. When you begin, she asks you some questions about your outlook on the world to get an understanding of you. In fact, her questions are drawn from psychological profiling questionnaires. She - and the software - are profiling you and she gives you advice based on your answers.

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, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait "Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.

Personality profiles from facebook likes

Apply Magic Sauce is a non-profit academic research project coordinated by the University of Cambridge Psychometrics Centre. The demos and platforms available here are a modest attempt to reverse the trend in Big Data and empower citizens to not only retain control of their data but also derive meaningful insight from it.