Andrea Capocci

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A new mechanism leading to scale-free networks is proposed in this Letter. It is shown that, in many cases of interest, the connectivity power-law behavior is neither related to dynamical properties nor to preferential attachment. Assigning a quenched fitness value x(i) to every vertex, and drawing links among vertices with a probability depending on the(More)
We present an analysis of the statistical properties and growth of the free on-line encyclopedia Wikipedia. By describing topics by vertices and hyperlinks between them as edges, we can represent this encyclopedia as a directed graph. The topological properties of this graph are in close analogy with those of the World Wide Web, despite the very different(More)
A. Capocci, V. D. P. Servedio, 1 F. Colaiori, L. S. Buriol, D. Donato, S. Leonardi, and G. Caldarelli 1 Centro Studi e Ricerche E. Fermi, Compendio Viminale, Roma, Italy Dipartimento di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Salaria 113, 00198 Roma, Italy CNR-INFM(SMC) Istituto dei Sistemi Complessi and Dipartimento di Fisica,(More)
We analyze here a particular kind of linguistic network where vertices represent words and edges stand for syntactic relationships between words. The statistical properties of these networks have been recently studied and various features such as the small-world phenomenon and a scale-free distribution of degrees have been found. Our work focuses on four(More)
In this paper we investigate the nature and structure of the relation between imposed classifications and real clustering in a particular case of a scale-free network given by the on-line encyclopedia Wikipedia. We find a statistical similarity in the distributions of community sizes both by using the top-down approach of the categories division present in(More)
We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tripartite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between(More)
We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and links orientations. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable to the analysis of social and(More)
We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and(More)
The hierarchical structure of scale-free networks has been investigated focusing on the scaling of the number N(h)(t) of loops of size h as a function of the system size. In particular, we have found the analytic expression for the scaling of N(h)(t) in the Barabási-Albert (BA) scale-free network. We have performed numerical simulations on the scaling law(More)
Folksonomies provide a rich source of data to study social patterns taking place on the World Wide Web. Here we study the temporal patterns of users' tagging activity. We show that the statistical properties of inter-arrival times between subsequent tagging events cannot be explained without taking into account correlation in users' behaviors. This shows(More)