Washington: Accurate estimates of Facebook users` race, age, IQ, sexuality, personality, substance use and political views can be inferred from automated analysis of only their `Likes` on the social networking site, a research has revealed.
In the new study, published in the journal PNAS, researchers described Facebook Likes as a "generic class" of digital record, and suggested that such techniques could be used to extract sensitive information for almost anyone regularly online.
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. Users opted in to provide data and gave consent to have profile information recorded for analysis.
Models proved 88 percent accurate for determining male sexuality, 95 percent accurate distinguishing African-American from Caucasian American and 85 percent accurate differentiating Republican from Democrat.
Christians and Muslims were correctly classified in 82 percent of cases, and good prediction accuracy was achieved for relationship status and substance abuse, between 65 and 73 percent.
But few users clicked Likes explicitly revealing these attributes.
For example, less that 5 percent of gay users clicked obvious Likes such as Gay Marri age.
While they highlight the potential for personalised marketing to improve online services using predictive models, the researchers also warn of the threats posed to users` privacy.