As stated in our article for The Conversation, reaching an agreement is a difficult task, especially if it involves large groups of individuals with a diversity of opinions, tendencies and interests. We have now an explanation for this, based on the scientific modelling of opinion dynamics in social systems. The results of our investigation, published in…
We introduce D-Mercator, a model-based embedding method that produces multidimensional maps of real networks into the (D + 1)-hyperbolic space, where the similarity subspace is represented as a D-sphere. Multidimensional representations of real networks are instrumental in the identification of factors that determine connectivity and in elucidating fundamental issues that hinge on dimensionality.
In our paper Geometric description of clustering in directed networks we extend our geometric framework to describe real directed networks. The model is able to reproduce the spectrum of all types of directed triangles from real networks with astonishing accuracy.
