Community discovery in complex networks is an interesting
problem with a number of applications, especially in the knowledge
extraction task in social and information networks. However, many
large networks often lack a particular community organization at a
global level. In these cases, traditional graph partitioning
algorithms fail to let the latent knowledge embedded in modular
structure emerge, because they impose a top-down global view of a
network. DEMON is a simple local-first approach to community
discovery, able to unveil the modular organization of real complex
networks. This is achieved by democratically letting each node vote
for the communities it sees surrounding it in its limited view of the
global system, i.e. its ego neighborhood, using a label propagation
algorithm; finally, the local communities are merged into a global
collection.
NOTE: This seminar belongs to the series of seminars presented by the
winners of the prize "Young researchers ISTI 2013". Giulio Rossetti
placed second in the PhD student category
.
