One of the more interesting reveals that Dan Francis, Senior Product Manager for LinkedIn Talent Insights, provided in a recent talk about the Talent Insights tool is how LinkedIn is using machine learning to determine skills of people. He says that there are now over 575 million members in the LinkedIn database and there are 35,000 standardized skills in LinkedIn’s skills taxonomy. The way LinkedIn is figuring out what skills a member has is via machine learning technology.

Dan Francis, Senior Product Manager, LinkedIn Talent Insights, discussed Talent Insights in a recent LinkedIn video embedded below:

LinkedIn Using Machine Learning to Determine Skills

The skills data in Talent Insights comes from a variety of sources, mainly from a member’s profile. There are over 35,000 standardized skills that we have in LinkedIn’s skills taxonomy, and the way we’re figuring out what skills a member has is using machine learning. We can identify skills that a member has that’s based on things that they explicitly added to their profile.

The other thing that we’ll do is look at the text of the profile. There’s a field of machine learning called natural language processing and we’re basically using that. It’s scanning through all the words that are on a member’s profile, and when we can determine that it’s pertaining to the member, as oppose the company or another subject, we’ll say okay, we think that this member has this skill. We also look at other attributes, like their title or the company, to make sure they actually are very likely to have that skill.

The last thing that we’ll do is look at the skills a member has and figure out what are skill relationships. So as an example, let’s say that a member has Ember, which is a type of JavaScript framework, since we know that they know Ember, they also know JavaScript. So if somebody’s running a search like that, we’ll surface them in the results. I think that the most important reason why this is helpful and the real benefit to users of the platform is when you’re searching, you want to get as accurate a view of the population as possible. What we’re trying to do is look at all the different signals that we possibly have to represent that view.  

575 Million People on LinkedIn Globally and Adding 2 Per Second

Today, LinkedIn has over 575 million members that are on the platform globally. This is actually growing at a pretty rapid clip, so we’re adding about two members per second. One of the great things about LinkedIn is that we’re actually very well represented in terms of the professional workforce globally. If you look at the top 30 economies around the world, we actually have the majority of professionals in all of those economies.

LinkedIn is the World’s Largest Aggregator of Jobs

I think there’s often a perception that most of the data’s directly from LinkedIn, stuff that’s posted on LinkedIn and job status is one notable exception to that. Plenty of companies and people will post jobs on LinkedIn, and that’s information that does get surfaced. However, we’re also the world’s largest aggregator of jobs. At this point there are over 20 million jobs that are on LinkedIn.

The way that we’re getting that information is we’re working with over 40,000 partners. These are job boards, ATS’s, and direct customer relationships. We’re collecting all of those jobs, standardizing them, and showing them on our platform. The benefit is not just for displaying the data in Talent Insights, the benefit is also when members are searching on LinkedIn.com, we’re giving them as representative a view of the job market as possible.