If you want a new job, don’t just rely on friends or family. According to one of the most influential theories in the social sciences, you are more likely to land a new position through your “weak links,” free acquaintances with whom you have few mutual connections. Sociologist Mark Granovetter first put forward this idea in a 1973 paper which has garnered more than 65,000 citations. But a theory called “the power of weak ties” after the title of Granovetter’s study, causal evidence was lacking for decades. Now a large-scale study that looks at more than 20 million people of the professional social networking site LinkedIn over a period of five years finally shows that creating weak links really does help people find new jobs. And it reveals which types of connections are most important to job seekers.
The power of weak ties “is really a cornerstone of social science,” said Dashun Wang, a professor at Northwestern University’s Kellogg School of Management who was not involved in the new study. For the original 1973 study, Granovetter interviewed people at the end of their careers and asked them about their experiences of changing jobs. Before his groundbreaking paper, many assumed that new positions came from sources such as close personal friends who would put in a good word, headhunters who would look for strong candidates, or public advertisements. But Granovetter’s analysis showed that people actually get a new job most often through friends of friends — often someone the job seeker didn’t know before they started looking for a new position. “It really shook people up because the assumptions about how people find the best jobs in life don’t seem to be true — it seems that strangers may actually be your best contacts,” says Brian Uzzi, also a professor at the Kellogg School of Management. , who was not involved in the new study.
What gives strangers an edge over friends? Granovetter posits that close connections—people in the same circle—largely have the same facts and professional opportunities at their disposal. But people who belong to different communities can offer a whole new set of information and useful links. A mutual friend can act as a bridge, connecting the job seeker with a contact in a different group, which provides new opportunities.
This explanation is based on observational evidence showing a relationship between weak ties and labor mobility. But correlation isn’t causation, and in the nearly 50 years since Granovetter first proposed his idea, researchers hadn’t proven that applicants’ weak ties were the specific thing that made them grab that new job. Two decades ago, when he was a graduate student, Sinan Aral could not help but notice this gap. “There’s a 500-pound gorilla in the middle of the room with this literature, which means we don’t have any causal evidence for any of these theories,” says Aral, the new study’s senior author, who is now a professor of management at MIT. institute. “We don’t know if weak ties are related to kindness [such as new jobs] because weak ties are good in themselves, or because people who form weak ties have some unobserved characteristics that also make them more productive, have good ideas, and get better jobs, promotions, and salaries.” As Wang says , “People use this theory and related concepts to explain a wide range of phenomena, but there has been no causal test of whether weak ties are causally related to job opportunities. And that’s what this paper does. The survey was published in Science in Thursday.
Developing experimental proof of this theory is extremely challenging. To test causality with the rigor of a randomized clinical trial, researchers would have to take two equivalent groups of people, experimentally manipulate their social networks by giving one group more weak ties and the other less, and then observe whether groups had different outcomes. But Aral and his colleagues discovered that LinkedIn already did something almost as good. As the engineers at the professional networking site tweaked the People You May Know recommendation algorithm, they ended up running very natural social experiments. In one case, LinkedIn will randomly vary the number of weak connections, strong connections, and total recommendations it displays for users, where the strength of the connection depends on the ratio of mutual to non-reciprocal connections. This provided a perfect experiment to test Granovetter’s idea. The researchers, led by LinkedIn applied research scientist Karthik Rajkumar and MIT graduate student Guillaume Saint-Jacques, analyzed this data over five years, comparing LinkedIn users who were algorithmically given more recommendations for weak ties (and therefore formed -weak links) with those who received stronger link offers. They then assessed how the addition of a strong or weak tie affected subjects’ subsequent job mobility. Thanks to LinkedIn’s algorithmic experiments, the team can discern the impact of equality strength than that of the total number of new connections.
The results not only support Granovetter’s theory, but also add several clarifications. First, not all weak ties were equally beneficial. If the strength of a relationship depends on the number of mutual contacts, then moderately weak ties, where two people share approximately 10 acquaintances, are of greatest importance. But the strength of ties can also be measured by the intensity of interaction, or the frequency with which you contact your weakly tied acquaintance. When researchers examine this metric, they find that the most useful connections are those that people don’t interact with very often. Finally, the team found that these effects vary by industry: LinkedIn’s weak ties are particularly beneficial in digital industries, which typically involve machine learning, artificial intelligence, robotics, software use, and remote and hybrid work, compared to “analog” ones. industries that require personal presence.
These results may be of benefit to job seekers considering how to build and grow their social networks. For example, when it comes to LinkedIn’s suggestions for people to connect with, “you might not want to ignore them,” Aral says. “And if you get a referral for someone and you don’t see what the connection might be,” it might still be worth looking into them. “It’s the … weak ties that can actually be the source of your next job,” he adds.
Despite these results, it’s important not to overlook the strong connections, Wang says. This study focuses on successes—ie. the people who got a new job. But it doesn’t explore all the failures and rejections that happened before success. To continue the grueling job search, we need strong ties to provide social support. “Just looking at the successes will only tell us part of the story,” notes Wang. “To be really successful in the end, you really need your strong ties.” Those strong ties are vital for groups like immigrants, who often form tight-knit communities to deal with discrimination and other pressures they experience. But it also means they may have a harder time accessing weak link opportunities. “Some of the things that hold immigrant groups or disadvantaged groups back is the very fact that it’s harder for them to have those weak ties,” Uzzi says.
Along with job seekers, politicians can also learn from the new document. “One thing the study highlights is the extent to which algorithms drive fundamental, basic, important outcomes like employment and unemployment,” says Aral. The role that LinkedIn’s People You May Know feature plays in finding a new job demonstrates “the enormous impact that algorithms are having on employment and possibly other factors in the economy.” He also suggests that such algorithms could create leads for economic change: In the same way that the Federal Reserve looks at the consumer price index to decide whether to raise interest rates, Aral suggests, networks like LinkedIn could provide new sources of data to help policy makers analyze what is happening in the economy. “I think these digital platforms will be an important source of that,” he says.