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LinkedIn conducts secret study on 20 million users

LinkedIn, Marquette University, Massachusetts Institute of Technology, Stanford University, Harvard Business School

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LinkedIn conducts secret study on 20 million users

LinkedIn conducted a secret experiment on 20 million of its users without their knowledge which may have had an impact on their ability to find work.

In a study published in Science, researchers from LinkedIn, the Massachusetts Institute of Technology, Stanford University and Harvard Business School revealed that a number of tests had been conducted on LinkedIn around the world from 2015 to 2019.

These tests involved changes to the algorithm used by LinkedIn to generate users for the “People You May Know” feature, increasing and decreasing the number of “weak” and “strong” contacts put forward for the connection, as the New York Times reported.

The purpose of this A/B testing was to test the “strength of weak ties” theory, which says that people are more likely to find work opportunities through lesser known acquaintances rather than through close friends.

The testing was done on 20 million LinkedIn users in total, who were not told they were test subjects, and revealed that minor adjustments can have an impact on someone’s ability to find a job.

“The findings suggest that some users had better access to job opportunities or a meaningful difference in access to job opportunities,” Centre for Data, Ethics and Society at Marquette University director Michael Zimmer said.

“These are the kind of long-term consequences that need to be contemplated when we think of the ethics of engaging in this kind of data research.”

LinkedIn has said in a statement that it “acted consistently with” its user agreement, privacy policy and member settings in doing the study.

The company’s privacy policy states that user data may be used for research purposes, and LinkedIn said that it used the latest “non-invasive” social science techniques “without any experimentation on members”.

The first wave of the testing took place in 2015 and involved more than 4 million experimental subjects. The second lot of testing was in 2019 and involved more than 16 million users.

The experiment focused on the People You May Know algorithm, which hoovers up data such as a user’s employment history, job titles and ties to other users to gauge the likelihood they would send a connection request to another user, and the chances it would be accepted.

The experiment involved this algorithm being adjusted to show more or less “weak ties” in these recommendations.

The study served to confirm the strength of weak ties theory, finding that users who received more recommendations for moderately weak contacts typically applied for and accepted more jobs.

The 20 million users involved with the study generated more than 2 billion new connections on the platform and completed more than 70 million job applications which led to 600,000 new jobs.

The weak(est) link

The researchers found that it was the weak tie connections which proved most useful for LinkedIn users, particularly those working in tech industry such as artificial intelligence.

For those working in areas less reliant on software, strong ties proved to be more useful.

“The experiments showed that weak ties increase job transmission, but only to a point, after which there are diminishing marginal returns to tie weakness,” the study said.

“The authors show that the weakest ties had the greatest impact on job mobility, whereas the strongest ties had the least.”

MIT management and data science professor Sinan Aral said the LinkedIn study backed up the theory in question.

“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.”

“To do an experiment on 20 million people and to then roll out a better algorithm for everyone’s job prospects as a result of the knowledge that you learn from that is what they are trying to do. Rather than anointing some people to have social mobility and others to not.”

The secretive nature of the study and its potential to have a direct impact on an individual’s chances of securing employment has generated controversy.

LinkedIn applied research scientist Karthik Rajkumar said the aim of the study was to “help people at scale” and that “no-one was put at a disadvantage to find a job”.

In a disclaimer to the study, Science said that “the experiments undertaken by LinkedIn operated under the guidelines of their user agreements”.

Contents published under this byline are those created by the news team of BLiTZ

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