领英用两千万用户做了一场社会试验

Researchers examined changes that LinkedIn had made to its “People You May Know” algorithm to test what sociologists call the “strength of weak ties.”

The study maintains that people are more likely to gain employment and other opportunities through arms-length acquaintances than through close friends.

The researchers analyzed how LinkedIn’s algorithmic changes had affected users’ job mobility. They found that relatively weak social ties on LinkedIn proved twice as effective in securing employment as stronger social ties.

Sinan Aral, a management and data science professor at M.I.T. who was the lead author of the study, said LinkedIn’s experiments were an effort to ensure that users had equal access to employment opportunities.

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

For the experiments, LinkedIn adjusted its algorithm to randomly vary the prevalence of strong and weak ties that the system recommended. The first wave of tests, conducted in 2015, “had over four million experimental subjects,” the study reported. The second wave of tests, conducted in 2019, involved more than 16 million people.

During the tests, people who clicked on the “People You May Know” tool and looked at recommendations were assigned to different algorithmic paths. Some of those “treatment variants,” as the study called them, caused LinkedIn users to form more connections to people with whom they had only weak social ties. Other tweaks caused people to form fewer connections with weak ties.

The outside researchers analyzed aggregate data from LinkedIn. The study reported that people who received more recommendations for moderately weak contacts generally applied for and accepted more jobs — results that dovetailed with the weak-tie theory.

In fact, relatively weak contacts — that is, people with whom LinkedIn members shared only 10 mutual connections — proved much more productive for job hunting than stronger contacts with whom users shared more than 20 mutual connections, the study said.

Professor Aral of M.I.T. said the deeper significance of the study was that it showed the importance of powerful social networking algorithms — not just in amplifying problems like misinformation but also as fundamental indicators of economic conditions like employment and unemployment.

LinkedIn’s algorithmic experiments may come as a surprise to millions of people because the company did not inform users that the tests were underway.

The changes made by LinkedIn are indicative of how such tweaks to widely used algorithms can become social engineering experiments with potentially life-altering consequences for many people. Experts who study the societal impacts of computing said conducting long, large-scale experiments on people that could affect their job prospects, in ways that are invisible to them, raised questions about industry transparency and research oversight.

Experiments on users by big internet companies have a checkered history. Eight years ago, a Facebook study describing how the social network had quietly manipulated what posts appeared in users’ News Feeds in order to analyze the spread of negative and positive emotions on its platform was published. The weeklong experiment, conducted on 689,003 users, quickly generated a backlash.

Critics disagreed, with some assailing Facebook for having invaded people’s privacy while exploiting their moods and causing them emotional distress. Others maintained that the project had used an academic co-author to lend credibility to problematic corporate research practices.

In a statement, Linkedin said during the study it had “acted consistently with” the company’s user agreement, privacy policy and member settings. The privacy policy notes that LinkedIn uses members’ personal data for research purposes. The statement added that the company used the latest, “non-invasive” social science techniques to answer important research questions “without any experimentation on members.”

Catherine Flick, a senior researcher in computing and social responsibility at De Montfort University in Leicester, England, described the study as more of a corporate marketing exercise.

“The study has an inherent bias,” Dr. Flick said. “It shows that, if you want to get more jobs, you should be on LinkedIn more.”