  This paper briefly presents several ways to understand the organization of a
large social network (several hundreds of persons). We compare approaches
coming from data mining for clustering the vertices of a graph (spectral
clustering, self-organizing algorithms. . .) and provide methods for
representing the graph from these analysis. All these methods are illustrated
on a medieval social network and the way they can help to understand its
organization is underlined.
