Your Facebook Like Speaks Aloud About You

SynapseIndia has been aggressively tracking the recent studies at the University of Cambridge about the `like` feature on Facebook that can reveal a lot about the end user. One can know more about the personality of an individual, their sexual orientation, IQ level, religious beliefs, and several other traits by studying through their likes and dislikes. "This study demonstrates the degree to which relatively basic digital records of human behavior can be used to automatically and accurately estimate a wide range of personal attributes that people would typically assume to be private," researchers said in the study, which was published today in Proceedings of the National Academy of Sciences.

If you tend to like something and have posted a comment on the same, the recorded data can be calibrated by machines in such a manner that it can reveal several traits with utmost accuracy. Several predictors can also speak of whether the parents of the user were divorced when young or whether they hadn't.  Every result provided is first corroborated with the information that is provided on the profiles of each user. "Each person, on average, liked 170 things," says psychologist Michal Kosinski, the study's lead author. "Some liked only one thing and there were people who liked thousands of things. We removed those. We looked at people who liked between one and 700 different things."

The precision of this study has be confirmed at SynapseIndia through the results that were provided. According to which they were able to correctly classify 95% users on the basis of ethnic origin and gender. Similarly 93% of the users were correctly classified as males and females. Even sexual orientation was easy to determine, with 88% of males and 75% of females being judged correctly. "This is not unique to Facebook and is not even unique to social networking in general," says David Jacobs, consumer privacy counsel for the Electronic Privacy Information Center, a public interest research center in Washington. "It's one of the implications of Big Data and in this case Big Data in a social networking context. Lots of information makes for certain inferences and sensitive predictions."

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