Data Science of the Facebook World
(vía Stephen Wolfram Blog : )
Muy interesante esta parte también:
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The first step is to find some kind of iconic summary of each network, which we can do for example by looking at the overall connectivity of clusters, ignoring their substructure. And so, for example, for Catherine (who happened to suggest this idea), this reduces her network to the following “cluster diagram”:
Doing the same thing for the Data Donor networks shown above, here’s what we get:
In making these diagrams, we’re keeping every cluster with at least 2 friends. But to get a better overall view, we can just drop any cluster with, say, less than 10% of all friends—in which case for example Catherine’s cluster diagram becomes just:
And now for example we can count the relative numbers of different types of structures that appear in all the Data Donor networks:
And we can look at how the fractions of each of these structures vary with age:
What do we learn? The most common structures consist of either two or three major clusters, all of them connected. But there are also structures in which major clusters are completely disconnected—presumably reflecting facets of a person’s life that for reasons of geography or content are also completely disconnected.”
Linkedin, de la red social hacia el contenido - Error 500
Es interesante la deriva, sí. Tal vez tratan de ser más atractivos para más gente y de esta manera conseguir que los ‘reclutadores’ tengan más donde elegir… Tampoco es despreciable la tentación de tratar de hacerse con la puerta de entrada a internet (profesional, la otra seguramente sea facebook).
También está el juego de los ‘endorsements’ y otros experimentos que van lanzando de vez en cuando…
