LinkedIn is a great resource for exploring professional profiles. However, when your personal social network starts to grow into the hundreds of contacts, it becomes very hard to – quite literally – still see the bigger picture. One feature that can help you visualize your network is LinkedIn Maps. It both shows the links between your connections and color-codes major clusters that are rough approximations of the various professional and personal worlds you move around in. You can zoom in and out, and select individual contacts to see which persons you know they are also connected to.
Of course, it makes for pretty art. However, the maps can also be useful. First, they give you a quick sense of the roles you play in your social world, through the colored sub-networks. Another use is to find out which people who you think don’t know one another, in fact are acquainted.
To give you an idea of what LinkedIn Maps is about in practice, here are some of my own maps. First, the total overview, showing the “regions of my personal world map” (click on the figures to see the details). For instance, one big region is formed by my local Tilburg connections, other regions by my Tilburg University research contacts, my international Community Informatics research connections, etc.
The closer the regions are to my own node, and the more densely connected they are, the more they represent my “daily social circles”. When zooming in, the names of individual connections become visible. The bigger the dots depicting my contacts, the more they are connected to my own contacts, and the more likely we have something in common, if only by knowing the same people.
Finally, by selecting particular contacts, you can quickly explore which of your contacts in the various regions you share. This can be very valuable information, in, for example, setting up joint projects, selecting network coordinators or community managers who need to act as “spiders in your webs”, and so on. In this figure, I have selected one of my close contacts, and immediately see he is quite evenly connected to all of my “daily networks”. If I were to set up a project involving those networks, he would be a good candidate to ask for assistance.
On the other hand, the contact I selected in this example, is very much connected to many of the people in my subnetwork that I have dubbed my “Tilburg University research network”. So, if I were to set up a joint research project with my former colleagues, he would be one of the persons to talk to first!
Making CommunitySense 
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