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 M.I.T. 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.
The strength of weak ties
Researchers were testing a social-scientific theory known as the "strength of weak ties," which Sinan Aral, an award-winning management and data science professor at M.I.T. and lead author of the study, said "is one of the most influential social science theories of the last century."
In that theory from Stanford professor Mark Granovetter, there are weak ties, like friends of friends, and strong ties, like immediate colleagues. His research posits it's those weak ties that can lead you to better job opportunities not found in your strong ties network.
Strong ties can be "confining" to "small, well-defined groups," like how you probably know the close friends of your close friends.
The LinkedIn study "surprisingly" confirmed this theory, Aral said.
"Acquaintances are more valuable sources of job opportunities," Aral said. "We also found that it's not the weakest ties but moderately weak ties, which are the best."
The strength of these weak ties varied across industries..
"The findings help us understand how platform algorithms affect employment opportunities and outcomes and help LinkedIn design their platform to more effectively help its members find jobs and achieve social and economic mobility," Aral said.
A question of ethics
Privacy advocates told the New York Times Sunday that some of the 20 million LinkedIn users may not be happy that their data was used without consent. That resistance is part of a longstanding pattern of people's data being tracked and used by tech companies without their knowledge.
LinkedIn did not respond to an email sent by USA TODAY on Sunday.
That access can be used "to conduct research and development for our Services in order to provide you and others with a better, more intuitive and personalized experience, drive membership growth and engagement on our Services, and help connect professionals to each other and to economic opportunity."
It can also be deployed to research trends.
The company also said it used "non-invasive" techniques for the study's research.
Aral told USA TODAY that researchers "received no private or personally identifying data during the study and only made aggregate data available for replication purposes to ensure further privacy safeguards."
"The study was vetted and approved by the M.I.T Committee on the Use of Human Subjects in research and these types of algorithm experiments, in addition to helping platforms improve, are also standard across the industry," Aral said.
LinkedIn is far from the first tech company to analyze its members' data without their knowledge.
In 2014, Facebook and researchers from the University of California and Cornell University upset people when it released results of a study that had silently manipulated people's News Feeds for a week in 2012.
The company said it wanted to see how positive content versus negative content affected people's emotions and Facebook usage.
But privacy advocates immediately pushed back on the study's methods. One professor called the study "psychological manipulation." Eventually, even the Facebook scientists who worked on the study apologized for "any anxiety it caused."
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