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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Malleability of complex networks

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Author(s):
Silva, Filipi N. [1] ; Comin, Cesar H. [2] ; Costa, Luciano da F. [3]
Total Authors: 3
Affiliation:
[1] Indiana Univ, Network Sci Inst, Bloomington, IN 47408 - USA
[2] Univ Fed Sao Carlos, Dept Comp Sci, Sao Carlos, SP - Brazil
[3] Univ Sao Paulo, Sao Carlos Inst Phys, Sao Carlos, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT; AUG 2019.
Web of Science Citations: 0
Abstract

Most complex networks are not static, but evolve along time. Given a specific configuration of one such changing network, it becomes a particularly interesting issue to quantify the diversity of possible unfoldings of its topology. In this work, we suggest the concept of malleability of a network, which is defined as the exponential of the entropy of the probabilities of each possible unfolding with respect to a given network configuration. In order to avoid the combinatorics involved by identifying isomorphisms, we calculate the malleability with respect to specific measurements of the involved topologies. More specifically, we identify the possible topologies derivable from a given configuration and calculate some topological measurements of them, such as clustering coefficient, shortest path length and assortativity, leading to respective probabilities being associated to each possible measurement value. Though this approach implies some level of degeneracy in the mapping from topology to measurement space, it still paves the way to inferring the malleability of specific network types with respect to given topological measurements. We report that the malleability, in general, depends on each specific measurement, with the average shortest path length and degree assortativity typically being characterized by large malleability values. For an edge removal dynamics, large malleability values were observed for the Barabasi-Albert, Erdos-Renyi and Waxman network models, while the Watts-Strogatz model resulted in the smallest malleability values. (AU)

FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants
FAPESP's process: 15/08003-4 - Complex network approach to e-Science and dynamic datasets
Grantee:Filipi Nascimento Silva
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 17/09280-7 - Probing the structure and dynamics of information networks
Grantee:Filipi Nascimento Silva
Support type: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 15/18942-8 - Associating Complex Networks with Effective Feature Spaces
Grantee:Cesar Henrique Comin
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:José Alberto Cuminato
Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 18/09125-4 - Representation, Characterization and Modeling of Biological Images Using Complex Networks
Grantee:Cesar Henrique Comin
Support type: Regular Research Grants
FAPESP's process: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants