When it comes to finding jobs and making professional connections via a social platform, LinkedIn wins hands down.
The app is user-friendly, free of cost, and oh so effective in getting what you want in this competitive professional world. But new research is highlighting some shocking findings.
LinkedIn has been accused of running a series of experiments on its users for the past five years. And they’ve been undercover this whole time.
The study was stated to have analyzed a whopping 20 million users of the app and that’s when it was able to deduce how your acquaintances are a bigger source of help in finding the perfect job than your best buddies.
So many researchers are currently behind the study and they claim the findings are designed to enhance job mobility through the app. But while the news is positive, the fact that the app was taking part in such massive research and collecting data and then studying it really irked plenty of people. After all, transparency is the rage these days and if you don’t get that, well, it can be an issue.
This particular study was published in a journal called Science and it was carried out by top names on LinkedIn, M.I.T, and Harvard’s Business School too. The research was undertaken in 2015 and extended to 2019.
This study highlighted how several large-scale trials were carried out on the algorithm of the app called ‘People You May Know.’ For those who may not be aware, the feature is designed to suggest all sorts of new connections to its users here.
The practice is called A/B testing and the trials entailed providing users with some close and other not-so-close recommendations. These were again analyzed and all types of new jobs that were related to nearly 2 billion connections were studied in detail.
Researchers appeared to be busy testing an age-old theory in the world of science called the ‘strength of weak ties.’ Weak ties are usually found to be your friends while strong ties include your best colleagues or co-workers. And the results of the study found that weaker ties performed better in terms of providing users with the best work opportunities. Hence, it was great to see the LinkedIn experiment confirm the study.
Who knew your acquaintances were the ones that would really prove to be bigger assets in this world right?
The research really helped the researchers understand how such algorithms on apps can impact various chances of employment. So now, the app can better assist its members in getting the right job opportunities while achieving economic mobility.
Those who support privacy were recently seen speaking to The New York Times and claiming how about 20 million LinkedIn members aren’t going to be happy with the news that their data was used and being tracked by firms without any knowledge. But the app acted in a consistent manner.
For now, LinkedIn is yet to respond to queries on the matter but a new report claims the app has all the rights to utilize users’ data on a personal level because it’s outlined in its policy.
H/T: NYT
Read next: New Report Shares The Mind-Blowing Amount of Data Swirling On The Internet In One Minute
The app is user-friendly, free of cost, and oh so effective in getting what you want in this competitive professional world. But new research is highlighting some shocking findings.
LinkedIn has been accused of running a series of experiments on its users for the past five years. And they’ve been undercover this whole time.
The study was stated to have analyzed a whopping 20 million users of the app and that’s when it was able to deduce how your acquaintances are a bigger source of help in finding the perfect job than your best buddies.
So many researchers are currently behind the study and they claim the findings are designed to enhance job mobility through the app. But while the news is positive, the fact that the app was taking part in such massive research and collecting data and then studying it really irked plenty of people. After all, transparency is the rage these days and if you don’t get that, well, it can be an issue.
This particular study was published in a journal called Science and it was carried out by top names on LinkedIn, M.I.T, and Harvard’s Business School too. The research was undertaken in 2015 and extended to 2019.
This study highlighted how several large-scale trials were carried out on the algorithm of the app called ‘People You May Know.’ For those who may not be aware, the feature is designed to suggest all sorts of new connections to its users here.
The practice is called A/B testing and the trials entailed providing users with some close and other not-so-close recommendations. These were again analyzed and all types of new jobs that were related to nearly 2 billion connections were studied in detail.
Researchers appeared to be busy testing an age-old theory in the world of science called the ‘strength of weak ties.’ Weak ties are usually found to be your friends while strong ties include your best colleagues or co-workers. And the results of the study found that weaker ties performed better in terms of providing users with the best work opportunities. Hence, it was great to see the LinkedIn experiment confirm the study.
Who knew your acquaintances were the ones that would really prove to be bigger assets in this world right?
The research really helped the researchers understand how such algorithms on apps can impact various chances of employment. So now, the app can better assist its members in getting the right job opportunities while achieving economic mobility.
Those who support privacy were recently seen speaking to The New York Times and claiming how about 20 million LinkedIn members aren’t going to be happy with the news that their data was used and being tracked by firms without any knowledge. But the app acted in a consistent manner.
For now, LinkedIn is yet to respond to queries on the matter but a new report claims the app has all the rights to utilize users’ data on a personal level because it’s outlined in its policy.
H/T: NYT
Read next: New Report Shares The Mind-Blowing Amount of Data Swirling On The Internet In One Minute
