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How to use LinkedIn for data selection, in response to this problem, this article details the corresponding analysis and answer, hoping to help more small partners who want to solve this problem find a simpler and easier way.

LinkedIn is widely regarded as a social networking site for adults, gathering 259 million people around the world to post their resumes on the site. It was never intended to be a backyard for teenagers. Parents may like to post decades of work experience on it, but high school nannies and hamburger chefs don't like to use it to keep track of their temps.

When the data scientists came on board, things changed. In fact, in 2011, LinkedIn began to think about how to communicate with users under the age of 18. These teens may not contribute much to LinkedIn's 20-petabyte trove of career information, but they may be among the most avid consumers of data. Specifically, LinkedIn could open the door to where college graduates are going to work-giving these young people an analytical dashboard on which to bet on their future.

Take Carnegie Mellon University and Purdue University: LinkedIn collected career data on more than 60000 graduates from both universities. The amount of data is large enough to see clear patterns in it. Type "MIT," and you'll soon see that graduates of the university typically find jobs at Google, IBM, and Oracle. Enter "Purdue" and you'll find Lilly, Cummins and Boeing top the list for graduates.

Purvi Modi, a college counselor in Cupertino, Calif., points out that this kind of information is a gold mine for both seniors and juniors in high school, because most middle school students have only vague ideas about their future careers. Using LinkedIn's tool, students interested in solar energy, screenwriting, or medical devices can choose the universities where graduates are most likely to enter the relevant fields. Moody, who consults about 300 students each year, said about 40 percent of students now browse the section of LinkedIn's database called University Pages, hoping to get ideas. Considering that LinkedIn only started providing data combing services to the public in August 2013, this ratio is really amazing.

LinkedIn is profitable because of its large membership, and there are two ways to make money. First, recruiters pay $8500 a year to get more information about job seekers. Second, members can purchase premium services that make it easier to navigate the site. In the eyes of investors, LinkedIn may gain a near-monopoly position in the global recruitment market. As of January, LinkedIn had a market cap of $24.5 billion (an astonishing 728-fold annual growth rate). This suggests that Social networks are already beginning to exploit the value of their vast databases.

Such high valuations have also put pressure on LinkedIn's 68 data scientists to develop new tools to extract value from the vast number of bits. They have devised an algorithm that instructs recruiters to "find the people you want to hire," while other tools offer "jobs you might like" to ambivalent employees. Another example of this pattern is the "college page," which is a low-key version of "college you might want to go to."

Gloria Lau, LinkedIn's chief data scientist in charge of the project, said developing the right tools for university admissions was surprisingly tricky. They can't yet make a list of good colleges at once, because teenagers (and their parents) often don't have a clear idea of their ambitions at first.

Liu found that young people need to spend some time exploring for themselves. Initially, these students are interested in broad fields, such as engineering, and after testing various screening programs, they discover specific fields and related companies that they didn't know about before. Some of them may be interested in a mechanical engineer position offered by Tesla or Lockheed Martin, while others may learn that a local university can help them find a job as a petroleum engineer at Halliburton.

This "self-picking data" approach is slower and produces results that are harder to predict than LinkedIn's instant recommendations to job seekers. For LinkedIn, however, this is not entirely bad. Because university applicants will hang around the site, they are likely to see more advertisements and make better use of the site. In addition, allowing users to discover their own needs in the process of exploration can also prevent the website from giving special attention to some schools and making negative comments on others.

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