Not really - its finding those who connect most networks - the routers if you will.
From the article they remove those who have the most connections first. Lets say that if more than 10 of your LinkedIn links have photos, then you will upload one too. So they find everyone who has >10 friends, order them and remove the top 20% of most connected individuals. Then repeat. Stop when you have a group of people none of whom has >10 (extant) friends.
This group of people can then be given a virus (behaviour/whatever). Now put back the most recently removed group of people. It is guaranteed that each of those new people will all have 10+ friends all of whom exhibit this new virus.
Its pretty clever. Now I need to grab graph-tool and start playing !
Also:
> Lastly, we find that highly clustered local neighborhoods, together with dense network-wide community structures, suppress a trend's ability to spread under the tipping model.
That matters and frankly is the future of the internet. We shall most likely see geo-physical mesh neighborhoods. Always on, mobile or not, connectivity to the people around you. It probably will make a resurgance of democracy and community, likely to solve enourmous caching problems, and utterly destroy loads of business models. And yes ! its Maths and Science that proves its !
It seems to me that in the real world, this group would be people with the most friends, or people with very diverse friends, kind of a no-brainer.