Top influencers can be identified universally by combining classical centralities
Abstract Information flow, opinion, and epidemics spread over structured networks. When using node centrality indicators to predict which nodes will be among the top influencers or superspreaders, no single centrality is a consistently good ranker across networks. We show that statistical classifier...
Saved in:
Main Author: | Doina Bucur |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2020
|
Subjects: | |
Online Access: | https://doaj.org/article/19708cbb8fc8425c8894a545b74efcf3 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Endodontic Microbiology: A Bibliometric Analysis of the Top 50 Classics
by: Mohmed Isaqali Karobari, et al.
Published: (2021) -
Genome-wide scan identifies loci associated with classical BSE occurrence.
by: Brenda M Murdoch, et al.
Published: (2011) -
Top-down influences of the medial olivocochlear efferent system in speech perception in noise.
by: Srikanta K Mishra, et al.
Published: (2014) -
Sample-based approach can outperform the classical dynamical analysis - experimental confirmation of the basin stability method
by: P. Brzeski, et al.
Published: (2017) -
Characterizing the interactions between classical and community-aware centrality measures in complex networks
by: Stephany Rajeh, et al.
Published: (2021)