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- Dmitri V. Krioukov, Fragkiskos Papadopoulos, Maksim Kitsak, Amin Vahdat, Marián Boguñá
- Physical review. E, Statistical, nonlinear, and…
- 2010

We develop a geometric framework to study the structure and function of complex networks. We assume that hyperbolic geometry underlies these networks, and we show that with this assumption, heterogeneous degree distributions and strong clustering in complex networks emerge naturally as simple reflections of the negative curvature and metric property of the… (More)

- Marián Boguñá, Romualdo Pastor-Satorras, Albert Díaz-Guilera, Alex Arenas
- Physical review. E, Statistical, nonlinear, and…
- 2004

We propose a class of models of social network formation based on a mathematical abstraction of the concept of social distance. Social distance attachment is represented by the tendency of peers to establish acquaintances via a decreasing function of the relative distance in a representative social space. We derive analytical results (corroborated by… (More)

- Marián Boguñá, Dmitri V. Krioukov, Kimberly C. Claffy
- ArXiv
- 2007

Routing information through networks is a universal phenomenon in both natural and manmade complex systems. When each node has full knowledge of the global network connectivity, finding short communication paths is merely a matter of distributed computation. However, in many real networks nodes communicate efficiently even without such global intelligence.… (More)

We review the behavior of epidemic spreading on complex networks in which there are explicit correlations among the degrees of connected vertices.

- Marián Boguñá, Romualdo Pastor-Satorras
- Physical review. E, Statistical, nonlinear, and…
- 2003

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices.… (More)

- Ma Angeles Serrano, Marián Boguñá
- Physical review. E, Statistical, nonlinear, and…
- 2003

Economy, and consequently trade, is a fundamental part of human social organization which, until now, has not been studied within the network modeling framework. Here we present the first, to the best of our knowledge, empirical characterization of the world trade web, that is, the network built upon the trade relationships between different countries in… (More)

- Fragkiskos Papadopoulos, Marián Boguñá, Dmitri V. Krioukov
- Nature
- 2012

The principle that 'popularity is attractive' underlies preferential attachment, which is a common explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections possessed by nodes follows power laws, as observed in many real… (More)

- Fragkiskos Papadopoulos, Dmitri V. Krioukov, Marián Boguñá, Amin Vahdat
- INFOCOM
- 2010

We show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. Hyperbolic geometry facilitates maximally efficient greedy forwarding in these networks. Greedy forwarding is topology-oblivious. Nevertheless, greedy packets find their destinations with 100% probability following almost optimal shortest paths. This… (More)

- Joan Serrà, Alvaro Corral, Marián Boguñá, Martín Haro, Josep Lluís Arcos
- Scientific reports
- 2012

Popular music is a key cultural expression that has captured listeners' attention for ages. Many of the structural regularities underlying musical discourse are yet to be discovered and, accordingly, their historical evolution remains formally unknown. Here we unveil a number of patterns and metrics characterizing the generic usage of primary musical facets… (More)

- Marián Boguñá, Romualdo Pastor-Satorras, Alessandro Vespignani
- Physical review letters
- 2003

Random scale-free networks have the peculiar property of being prone to the spreading of infections. Here we provide for the susceptible-infected-susceptible model an exact result showing that a scale-free degree distribution with diverging second moment is a sufficient condition to have null epidemic threshold in unstructured networks with either… (More)