InMaps is such an exciting new feature of LinkedIn – it’s occupied my thinking on Personal Networks for the last couple of days since writing my original post on the subject. DJ Patil is the Chief Scientist at LinkedIn – and seems to have been in charge of driving this project. Watch this video to see him explaining his network (and those of a couple of others) – with the advantage of a very large piece of paper!
It’s fascinating to see that this rich map has been algorithmically defined on connections – and does not use the metadata (often inconsistent) input by LinkedIn users.
Over at Flowdata (the very best place to find updates on visualisation) – DJ took time to comment on the blog post by Nathan Yau (Flowdata’s founder). He said:
One thing that we should note about the calculation is that this only uses the “graph” of connections. We don’t use any other information. I think that is one of the very powerful aspects of this visualization. For example, in my case, it identifies my wife’s networks, students, people I went to grad school with, etc. Additionally there are a couple of reasons why this was a challenge. A) Getting everything to work in the browser in a smooth way from small networks (come on Nathan you need to add some connections :-)) to larger networks. B) The ability to “process” as many user’s networks as they use the site. There are over 85M users and that requires some serious processing power. We’ll do a more extensive write up when we can and I can say I was surprised by how much compute power we had to apply to make this real.
DJ’s key points are that the “groups” of different colours are formed by connections. He also discussed the challenges of implementing this sort of visualisation to the huge LinkedIn following. Would be interested to see how the servers have performed the last couple of days.
Well done DJ – this is certainly a real help to my research on Personal Networks.
[…] This post was mentioned on Twitter by petermasters, Phil O'Brien, Phil O'Brien, Phil O'Brien, Phil O'Brien and others. Phil O'Brien said: @petor76 Hi Peter. Agree – visual stuff is great. You might like InMaps inventor DJ Patil showing his LinkedIn map: http://wp.me/pYnfH-7f […]
[…] can now get more info in my second post about InMaps – including video of DJ Patil giving further explanation of his network and development of […]
Great video, but now I’m motivated to flesh out my network so it actually reflects my connections. The networks he showed were huge!
I enjoy the visualization of the relationships. It helps readily surface patterns and (for me) gaps.
Hi Jeff. Thanks for reading and commenting. It’s great that the InMaps visualisation has given you a call to action. I think that many people’s reaction (judging by the twitter feeds on InMaps) is “it looks really pretty … BUT what does it mean?”. Glad you’ve found it useful. From the video, DJ has an advantage being able to print on to those HUGE sheets of paper – much easier to take in/navigate than my laptop screen.
My initial response to the graph was, “Wow, what a beautiful universe!” On further inspection, I tried to decipher how the the colors matched up to the connections, ones that overlapped, mutual relationships that I wasn’t aware of, and just how diverse my network really is. Thanks for the tweet Phil! It’s fascinating to see other graphs and how each is totally unique.
Hi Anandi. Thanks for taking time to read the blog. I think InMaps is definitely WOW – I’m imagining it like the first time a remote villager 250 years ago was shown an atlas of the world! It sounds like you’ve taken time out to trace some connections on your map – that’s what it’s all about stepping back and viewing the whole world. As you say, the great thing about a map of our Personal Network is that it is unique – our own universe. Appreciate your comment.