Study of the scientific impact of a synchrotron laboratory: coauthorship networks ...
Experimental study of the relevance of the structural network hubs on the catalyti...
Community detection in random network models for modeling brain data
Full text | |
Author(s): |
de Oliveira, Sandra Cristina
;
Ferreira, Taiane de Paula
;
Brigantini, Beatriz Barbero
Total Authors: 3
|
Document type: | Journal article |
Source: | ACTA SCIENTIARUM-TECHNOLOGY; v. 38, n. 3, p. 353-360, JUL-SEP 2016. |
Web of Science Citations: | 0 |
Abstract | |
A scientific co-authorship network may be modeled by a graph G composed of k nodes and m edges. Researchers that make up this network may be interpreted as its nodes and the link between these agents (co-authored papers) as its edges. Current work evaluated and compared the reliability measure of networks with two emphases: 1) On nodes (perfectly reliable edges) and 2) On edges (perfectly reliable nodes). Specifically, the reliability of a fictitious co-authorship network at a given time t was analyzed taking into account, first, the reliability of nodes (researchers) equal and different, and, second, the reliability of edges (co-authorship relations), equal and different. Additionally, centrality measures of nodes were obtained to identify situations where the insertion of an edge significantly increased the reliability of the network. Results showed that the reliability of the co-authorship network focusing on edges is more sensitive to changes in individual reliabilities than the reliability of the network focusing on nodes. Additionally, the use of centrality measures was viable to identify possible insertions of edges or co-authorship relations to increase the reliability of the network in the two approaches. (AU) | |
FAPESP's process: | 12/01690-8 - A study about reliability of systems under a social context |
Grantee: | Beatriz Barbero Brigantini |
Support Opportunities: | Scholarships in Brazil - Scientific Initiation |