From Captain €conomics (
Le Captain': Mais qui se cache derrière le masque du Captain'? Bruce Wayne? Peter Parker? Jean-Pierre Pernaut? Un lobbyiste de JP Morgan?...):
How is it possible to measure online influence on Twitter? And how to
identify the top 100 most influential Twitter accounts related to
economics? To address this issue, and following a methodology inspired
by the working paper "Measuring User Influence in Twitter: The Million Follower Fallacy",
we develop a pretty simple program in Python to extract data about
followership relation on Twitter, and we use an algorithm close to the
"Google PageRank" to classify and rank account by influence. We cluster
data using Force Atlas algorithm and we use Gephi to draw the
wonderfuuuuuul graph you'll see at the end of this article. But
how does it work more precisely? Let's try to explain this
step-by-step, using "nongeek" lexicon (if you just want to see the graph
and/or the final list, you can directly go to the end of this article)....MUCH MORE
Click through. Seriously.
