Network Analysis Based on Important Node Selection and Community Detection
Attila Mester,
Andrei Pop,
Bogdan-Eduard-Mădălin Mursa,
Horea Greblă,
Laura Dioşan and
Camelia Chira
Additional contact information
Attila Mester: Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Andrei Pop: Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Bogdan-Eduard-Mădălin Mursa: Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Horea Greblă: Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Laura Dioşan: Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Camelia Chira: Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
Mathematics, 2021, vol. 9, issue 18, 1-16
Abstract:
The stability and robustness of a complex network can be significantly improved by determining important nodes and by analyzing their tendency to group into clusters. Several centrality measures for evaluating the importance of a node in a complex network exist in the literature, each one focusing on a different perspective. Community detection algorithms can be used to determine clusters of nodes based on the network structure. This paper shows by empirical means that node importance can be evaluated by a dual perspective—by combining the traditional centrality measures regarding the whole network as one unit, and by analyzing the node clusters yielded by community detection. Not only do these approaches offer overlapping results but also complementary information regarding the top important nodes. To confirm this mechanism, we performed experiments for synthetic and real-world networks and the results indicate the interesting relation between important nodes on community and network level.
Keywords: network analysis; important nodes; community detection (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://www.mdpi.com/2227-7390/9/18/2294/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/18/2294/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:18:p:2294-:d:637546
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().