Entropic determination of the phase transition in a coevolving opinion-formation model.

We study an opinion formation model by the means of a coevolving complex network where the vertices represent the individuals, characterized by their evolving opinions, and the edges represent the interactions among them. The network adapts to the spreading of opinions in two ways: not only connected agents interact and eventually change their thinking but an agent may also rewire one of its links to a neighborhood holding the same opinion as his. The dynamics, based on a global majority rule, depends on an external parameter that controls the plasticity of the network.

Two classes of bipartite networks: nested biological and social systems.

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes.

Analysis and assembling of network structure in mutualistic systems.

It has been observed that mutualistic bipartite networks have a nested structure of interactions. In addition, the degree distributions associated with the two guilds involved in such networks (e.g.