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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.)

Robustness of community structure to node removal

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Author(s):
Amancio, Diego R. [1] ; Oliveira, Jr., Osvaldo N. [2] ; Costa, L. da F. [2]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Carlos, SP - Brazil
[2] Univ Sao Paulo, Sao Carlos Inst Phys, Sao Carlos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT; MAR 2015.
Web of Science Citations: 4
Abstract

The identification of modular structures is essential for characterizing real networks formed by a mesoscopic level of organization where clusters contain nodes with a high internal degree of connectivity. Many methods have been developed to unveil community structures, but only a few studies have probed their suitability in incomplete networks. Here we assess the accuracy of community detection techniques in incomplete networks generated in sampling processes. We show that the walktrap and fast greedy algorithms are highly accurate for detecting the modular structure of incomplete complex networks even if many of their nodes are removed. Furthermore, we implemented an approach that improved the time performance of the walktrap and fast greedy algorithms, while retaining the accuracy rate in identifying the community membership of nodes. Taken together our results show that this new approach can be applied to speed up virtually any community detection method in dense complex networks, as is the case for similarity networks. (AU)

FAPESP's process: 13/06717-4 - Modeling human knowledge and behavior with complex networks
Grantee:Diego Raphael Amancio
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 14/20830-0 - Using complex networks to recognize patterns in written texts
Grantee:Diego Raphael Amancio
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