Ruben Cuevas

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In this paper, we conduct a detailed measurement study to characterize and compare the " group-level " behavior of users in Facebook, Twitter and Google+. We focus on Popular, Cross (with account in three OSNs) and Random group of users in each OSN since they offer complementary views. We capture user behavior with the following metrics: user connectivity,(More)
Twitter is one of the most popular applications in the current Internet with more than 500 M registered users across the world. In this paper, we conduct a comprehensive analysis to understand the geographical characteristics of Twitter using cross-community mining techniques. Specifically, we study the locality level shown by the three main elements of(More)
Online social media has recently irrupted as the last major venue for the propagation of news and cultural content, competing with traditional mass media and allowing citizens to access new sources of information. In this paper, we study collectively filtered news and popular content in Twitter, known as Trending Topics (TTs), to quantify the extent to(More)
— The ICT (Information and Communication Technology) sector has recently been identified as a growing contributor to worldwide greenhouse gases emissions and power consumption. This has triggered interest for more energy efficient ways to design and operate telecommunication networks. We present an overview of the solutions proposed within the European(More)
— This work presents a study of searching mechanisms in Peer-to-Peer (p2p) networks. The aim of this research line is to analyse cross-searching mechanisms that will allow the hierarchical interconnection of p2p networks. A set of relevant metrics for interconnection scenarios are defined to evaluate scalability, robustness and routing latency.
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