For example, less that 5% of gay users clicked obvious Likes such as Gay Marriage. Christians and Muslims were correctly classified in 82% of cases, and good prediction accuracy was achieved for relationship status and substance abuse - between 65 and 73%.īut few users clicked Likes explicitly revealing these attributes. Models proved 88% accurate for determining male sexuality, 95% accurate distinguishing African-American from Caucasian American and 85% accurate differentiating Republican from Democrat. Researchers created statistical models able to predict personal details using Facebook Likes alone.

Users opted in to provide data and gave consent to have profile information recorded for analysis.įacebook Likes were fed into algorithms and corroborated with information from profiles and personality tests. Researchers at Cambridge's Psychometrics Centre, in collaboration with Microsoft Research Cambridge, analysed a dataset of over 58,000 US Facebook users, who volunteered their Likes, demographic profiles and psychometric testing results through the myPersonality application. In the study, researchers describe Facebook Likes as a 'generic class' of digital record - similar to web search queries and browsing histories - and suggest that such techniques could be used to extract sensitive information for almost anyone regularly online.

New research, published in the journal Proceedings of the National Academy of Sciences, shows that surprisingly accurate estimates of Facebook users' race, age, IQ, sexuality, personality, substance use and political views can be inferred from automated analysis of only their Facebook Likes - information currently publicly available by default.

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