New research from the University of Cambridge has painted an alarming picture of how innocuous digital behaviour can be used to infer intimate details and personality traits with an alarming degree of accuracy.

The new research shows how a user’s activity on social networking website Facebook can be used to accurate estimate a users’ race, age, IQ, sexuality, personality, substance use and political views by collating only their Facebook Likes, information which is publicly available.

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. Facebook Likes were fed into algorithms and corroborated with information from profiles and personality tests.

Researchers created statistical models able to predict personal details using Facebook Likes alone. 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.

Even seemingly opaque personal details such as whether users’ parents separated before the user reached the age of 21 were accurate to 60%, enough to make the information “worthwhile for advertisers”, suggest the researchers.