Proxies Fresh For Work

A fresh look at your business connections

Ali Imam: You'll already know, of course, that you know a lot of people at company X or Y. Or in my case, if you're looking at my map (above), that I know a ton of people from Carnegie Mellon. But what I might not have realized is how intermingled that group is or how separate they are from the rest of my professional career.

I used to work at Yahoo before I came to LinkedIn. If you look at my map, you can see there's a separate group within the Yahoo cluster in my network — that's the analytics team I used to work with. You can see that this group was more heavily connected to each other than the rest of Yahoo. I was able to piece together that this particular group is slightly different than the rest of Yahoo, even though, as part of the entire Yahoo team, they're all pretty close together.

Ali Imam: It's a simple premise. The idea is I'm grabbing all of the people I know, and I'm seeing who in my network they know — basically, how my contacts know each other. That's the only data I'm pulling into this. This is a purely data-driven product where you're looking at the intermingling of connections, and because of that, we're using some forces on that which push apart or attract based on those connections. And that's what forms the clusters you see in the map.

Because the people in my old Yahoo analytics team connected more to each other than the other folks at Yahoo that I've worked with, it makes sense that they're more tightly connected to each other. But there are also people that I worked with at Yahoo who are now also at LinkedIn, and you can see in my network that they're being pulled away from the Yahoo cluster and into my LinkedIn cluster. They're bridging these two groups. They're also green, as they're more highly connected to members of my Yahoo network than those in my LinkedIn network. Eventually they'll turn blue like the rest of my LinkedIn connections.

The data behind these maps is updated weekly. So if you visit every Monday or Tuesday, you'll have a lag of 20 seconds before something loads up because we're doing additional computation in the back before showing your network. You'll see changes over time. For example, a few weeks ago, my Carnegie Mellon network was split into two groups, but over the course of those two weeks, there was an alumni get-together back in Pittsburgh and a lot of my friends interconnected with each other and transformed those two groups into one group.

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