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A new study published in Science A new study of more than 20 million people shows that your close friends (on LinkedIn) aren’t your best bet: Instead, reach out to acquaintances you don’t know well enough to share a personal connection.
The experiments randomly varied the prevalence of weak ties in the networks of over 20 million people over a 5-year period, during which 2 billion new ties and 600,000 new jobs were created.
The experiments showed that weak attachment increases job transfers, but only to a point after which the marginal returns on attachment weakness decrease. The authors show that the weakest ties had the greatest impact on job mobility, while the strongest ties had the least.
In 1973, the American sociologist Mark Granovetter coined the phrase “the strength of weak bonds” in connection with social networks. He argued that the stronger the bonds between two people, the more their friendship networks overlap.
Simply put, you most likely know all of a close friend’s friends, but only a few friends of an acquaintance.
So if you’re looking for a job, you probably already know everything your immediate neighborhood has to offer. Intuitively, it’s the weak ties—your acquaintances—that provide the most opportunities for new discoveries.
acc ScienceThe strength of weak ties is an influential social science theory that emphasizes the importance of weak associations (e.g., acquaintance versus close friendship) in influencing information transmission through social networks.
Granovetter’s theory feels right, but is it? A team of researchers from LinkedIn, Harvard Business School, Stanford, and MIT set out to gather some empirical evidence on how weak attachment affects job mobility.
Their research drew on efforts by engineers at LinkedIn to test and improve the People You May Know platform’s recommendation algorithm. LinkedIn regularly updates this algorithm, which recommends new people to add to your network.
One of these updates tested the effects of encouraging the formation of strong bonds (recommending to add your close friends) versus weak bonds (recommending acquaintances and friends of friends). The researchers then followed the users who participated in this “A/B test” to see if the difference affected their employment results.
More than 20 million LinkedIn users worldwide have been randomly assigned to well-defined treatment groups. Users in each group were presented with slightly different new contact recommendations, resulting in users in some groups forming stronger bonds and users in other groups forming weaker bonds.
Next, the team measured how many jobs users in each group applied for and how many “job transfers” occurred. Job transfers are of particular interest as they are defined as obtaining a job at the same company as the new contact. A job transfer suggests the new contact helped land the job.
Using causal analysis, the study goes beyond simple correlations and connects linkages with employment. There are three key takeaways.
First, the recommendation engine has a significant impact on link building. Users who were recommended more weak links formed significantly more weak links, and users who were recommended more strong links formed stronger links.
Second, the experiment provides causal evidence that moderately weak ties are more than twice as effective as strong ties in helping a job seeker transition to a new employer. What is a “moderately” weak bond? The study found that job placements are most likely to come from acquaintances with whom you share about 10 mutual friends and rarely interact.
Third, the strength of weak ties varied by industry. While weak ties increased job mobility in more digitized industries, strong ties increased job mobility in less digital industries.
This LinkedIn study provides causal evidence for Granovetter’s thesis on the labor market for the first time. Causal analysis is key here, as large-scale studies of correlations between attachment strength and job transfer have shown that strong attachments are more beneficial, previously thought to be a paradox.
This study resolves the paradox and proves again the limitations of correlational studies, which work poorly at untangling confounders and sometimes lead to incorrect conclusions.
From a practical point of view, the study outlines the best parameters to suggest new links. It found that the connections that are most helpful when looking for a job are your acquaintances, people you meet at work, or friends of friends, rather than your closest friends—people with whom you have 10 or so contacts in common and who you are less likely to interact with on a regular basis.
These can be translated into algorithmic recommendations, making the recommendation engines of professional networks like LinkedIn even better at helping job seekers find jobs.
The public is often suspicious when large social media companies conduct experiments on their users (see Facebook’s infamous 2014 emotion experiment).
So, could LinkedIn’s experiment have harmed its users? Theoretically, users in the strong connections treatment group might have overlooked the weak connections that could have gotten them into their next job.
However, all groups had some level of occupational mobility – some slightly more than others. Because the researchers also observed a technical experiment, the study itself appears to raise few ethical concerns.
Nonetheless, it reminds us to question how much our most intimate professional decisions — like choosing a new career or a new job — are being driven by black-box artificial intelligence algorithms that we can’t see working.
(With inputs from PTI)
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