LinkedIn’s social experiments on millions of users raise ethical questions. All you need to know about them

Researchers evaluated data from "multiple large-scale randomized experiments" on the "People You May Know" algorithm of LinkedIn -- that recommends new connections to users.

"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," their paper said.

This meant they carried out split testing -- where one section of users were given an algorithm that suggested acquaintances as connections and other got suggestions to add close contacts.

The analysis showed that weak ties (acquaintances) were more helpful in getting jobs as compared to strong ties.

But weak ties help increase job transmissions only up to a certain point, after which there are "diminishing marginal returns to tie weakness".

"The authors show that the weakest ties had the greatest impact on job mobility, whereas the strongest ties had the least," the abstract of the study stated. "Together, these results help to resolve the apparent “paradox of weak ties” and provide evidence of the strength of weak ties theory."

According to a New York Times report, LinkedIn did not inform its users that it was conducting the tests. This has raised questions about ethics.

Experts said such experiments affect people's job prospects in hidden ways, the newspaper reported.

Meanwhile, LinkedIn said it used "noninvasive" techniques for the research, adding that it had acted in line with its privacy policy. The policy does say that LinkedIn can use data of its members to do research.