Marian Salzman (our Global CMO here at Porter Novelli) has had the inspired idea of getting people in the agency to tweet about the most exciting story this week (probably) — the inauguration of Barack Obama
You can see the results of the experiment on her blog.
I’m all for this, of course, for several reasons:
- It gets new people onto Twitter
- It helps us create a stronger network among Porter Novelli twitterers
- It means I can track who at the agency is on Twitter
Simply asking people doesn’t really work. Marian’s scheme gives us a shared sense of purpose, which is one of the criteria for creating a strong community. It’s a much better plan all round.
But — of course — I want to see whether I can track how that works in practice. What do the before and after photos of a strong community look like?
The map above is the “before” map. You can see that there’s some nice heavy clumping down in the bottom of the chart, but a lot of pendants towards the top of the graph — people who are held into the main network mainly because of @robmctree. If he were to leave the network, you can see that some of them would float away to become like the eight other unconnected nodes at the top left.
That’s why his node shows slightly “hotter” (we rank the nodes according to a colour scale from deep red at the coolest to white at the hottest.) The hotter the node, the higher its “betweenness centrality” (basically a measure of its structural significance – if you remove the nodes with high betweenness centrality, the network tends to fly apart faster than if you remove the others.)
@mediaczar (that’s me) is big and white. The size indicates how many other people in the network follow that user (me.) Normally the big nodes in a network have all the betweenness centrality.
What’s interesting is using this technique to identify those (like @robmctree, @noahbanning, @volapuk, @angie_s and @amytokes) who have relatively low link popularity but high structural significance.
Like finding “top bloggers”, finding “top twitterers” is relatively easy. But approaching them is harder: there may be more demands on their time, for one thing. But if we can identify those who are less “popular” but who may still carry lots of weight within the network, we may be able to find softer targets for our comms activities.
On another note: this project would never have happened without @mariansalzman, @tikkers, or @zeenat58 who have been tireless on the internal email channels. This only goes to show that mistaking the channel for the network is an error into which we can too easily fall.