activity
19982021
most citedSpreading gossip in social networks

145 citations · 510 across the 16 of their papers we have counts for

collaborators

16 papers

cond-mat.stat-mech2021★ 7 cited

Statistical mechanical approach of complex networks with weighted links

Rute Oliveira, Samuraí Brito, Luciano R. da Silva +1

Systems which consist of many localized constituents interacting with each other can be represented by complex networks. Consistently, network science has become highly popular in…

cond-mat.stat-mech2020★ 17 cited

Connecting complex networks to nonadditive entropies

R. M. de Oliveira, Samuraí Brito, L. R. da Silva +1

Boltzmann-Gibbs statistical mechanics applies satisfactorily to a plethora of systems. It fails however for complex systems generically involving strong space-time entanglement. It…

cond-mat.stat-mech2018★ 11 cited

Scaling properties of d-dimensional complex networks

Samuraí Brito, Thiago C. Nunes, Luciano R. da Silva +1

The area of networks is very interdisciplinary and exhibits many applications in several fields of science. Nevertheless, there are few studies focusing on geographically located $…

cond-mat.stat-mech2017★ 19 cited

Role of dimensionality in preferential attachment growth in the Bianconi-Barabási model

Thiago C. Nunes, Samurai Brito, Luciano R. da Silva +1

Scale-free networks are quite popular nowadays since many systems are well represented by such structures. In order to study these systems, several models were proposed. However, m…

cond-mat.stat-mech2015★ 51 cited

Role of dimensionality in complex networks: Connection with nonextensive statistics

S. G. A. Brito, L. R. da Silva, Constantino Tsallis

Deep connections are known to exist between scale-free networks and non-Gibbsian statistics. For example, typical degree distributions at the thermodynamical limit are of the form…

physics.soc-ph2014★ 1 cited

How to efficiently destroy a network with limited information

T. M. Vieira, G. M. Viswanathan, L. R. da Silva

We address the general problem of how best to attack and destroy a network by node removal, given limited or no prior information about the edges. We consider a family of strategie…