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.
Models proved 88% accurate for determining male sexuality, 95% accurate distinguishing African-American from Caucasian American and 85% accurate differentiating Republican from Democrat. 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%.
But few users clicked Likes explicitly revealing these attributes. For example, less that 5% of gay users clicked obvious Likes such as Gay Marriage. Accurate predictions relied on ‘inference’ — aggregating huge amounts of less informative but more popular Likes such as music and TV shows to produce incisive personal profiles.