Communications of the ACM
LinkedIn Ran Undisclosed Social Experiments on 20 Million Users for Years to Study Job Success
Privacy advocates said some of the 20 million LinkedIn users may not be happy that their data was used without consent.
Credit: dmexco.com
A new study analyzing the data of over 20 million LinkedIn users over the timespan of five years reveals that our acquaintances may be more helpful in finding a new job than close friends.
Researchers behind the study say the findings will improve job mobility on the platform, but since users were unaware of their data being studied, some may find the lack of transparency concerning.
Published this month in Science, the study was conducted by researchers from LinkedIn, Harvard Business School and the Massachusetts Institute of Technology between 2015 and 2019. Researchers ran "multiple large-scale randomized experiments" on the platform's "People You May Know" algorithm, which suggests new connections to users.
In a practice known as A/B testing, the experiments included giving certain users an algorithm that offered different (like close or not-so-close) contact recommendations and then analyzing the new jobs that came out of those two billion new connections.
From USA Today
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