The structure of the social networks in which individuals are embedded influences their political choices and therefore their voting behavior. Nowadays, social media represent a new channel for individuals to communicate, what together with the availability of the data, makes it possible to...

Over the past years, new technologies and specially online social networks have penetrated into the world’s population at an accelerated pace. In this paper we analyze collected data from the web application Twitter, in order to describe the structure and dynamics of the emergent social...

Complex networks are considered robust against random failures but sensitive to failures in target. Under this perspective we analyze the robustness of the Spanish telecommunication networks for digital transmission, the Synchronous Digital Hierarchy (SDH), considering failures in the equipments...

In this work we propose a dynamic network model based on an evolutive rule called compatibility. The presence of common topological properties observed in two real complex networks are well reproduced by the proposed model. These results suggest that the compatibility between nodes is sufficient...

In this paper we study the robustness of heterogeneous preferential attachment networks. The robustness of a network measures its structural tolerance to the random removal of nodes and links. We numerically analyze the influence of the affinity parameters on a set of ensemble-averaged...

In this paper we present a study of the influence of local affinity in heterogeneous preferential attachment (PA) networks. Heterogeneous PA models are a generalization of the Barabási–Albert model to heterogeneous networks, where the affinity between nodes biases the attachment probability...

In this paper we present a study of the connectivity degrees of the threshold preferential attachment model, a generalization of the Barabási–Albert model to heterogeneous complex networks. The threshold model incorporates the states of the nodes in its preferential linking rule and assumes...