Title: Correlation analysis: edge betweenness centrality vs. neighbourhood overlap

Authors: Natarajan Meghanathan; Fei Yang

Addresses: Jackson State University, Mailbox 18839, 1400 John R. Lynch Street, Jackson, Mississippi, MS 39217, USA ' Entergy, 740 South Street, Jackson, MS 39201, USA

Abstract: We explore the correlation between two well-known edge centrality metrics: a computationally-heavy metric called edge betweenness centrality (EBWC) and a computationally-light metric called neighbourhood overlap (NOVER). Three different correlation measures are used for the analysis: Spearman's correlation measure (for network-wide ranking), Kendall's correlation measure (for pair-wise relative ordering) and Pearson's correlation measure (for regression-based prediction). A suite of 47 real-world networks of diverse degree distributions have been used for the correlation study. Results of the correlation analysis indicate that NOVER could be used as a computationally-light alternative to rank the edges (network-wide) in lieu of EBWC, but might not be appropriate to predict the actual EBWC values.

Keywords: edge betweenness centrality; EBWC; neighbourhood overlap; NOVER; correlation; computationally-heavy; computationally-light.

DOI: 10.1504/IJNS.2019.102284

International Journal of Network Science, 2019 Vol.1 No.4, pp.299 - 324

Received: 12 Mar 2018
Accepted: 20 Aug 2018

Published online: 11 Sep 2019 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article