Next Article in Journal
A Decentralized Receiver in Gaussian Interference
Next Article in Special Issue
Network Entropy for the Sequence Analysis of Functional Connectivity Graphs of the Brain
Previous Article in Journal
Nash Bargaining Game-Theoretic Framework for Power Control in Distributed Multiple-Radar Architecture Underlying Wireless Communication System
Previous Article in Special Issue
Sparse Power-Law Network Model for Reliable Statistical Predictions Based on Sampled Data
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Entropy 2018, 20(4), 268;

Distance Entropy Cartography Characterises Centrality in Complex Networks

Fondazione Bruno Kessler, Via Sommarive 18, 38123 Povo, Italy
Authors to whom correspondence should be addressed.
Received: 28 February 2018 / Revised: 4 April 2018 / Accepted: 5 April 2018 / Published: 11 April 2018
(This article belongs to the Special Issue Graph and Network Entropies)
Full-Text   |   PDF [809 KB, uploaded 3 May 2018]   |  


We introduce distance entropy as a measure of homogeneity in the distribution of path lengths between a given node and its neighbours in a complex network. Distance entropy defines a new centrality measure whose properties are investigated for a variety of synthetic network models. By coupling distance entropy information with closeness centrality, we introduce a network cartography which allows one to reduce the degeneracy of ranking based on closeness alone. We apply this methodology to the empirical multiplex lexical network encoding the linguistic relationships known to English speaking toddlers. We show that the distance entropy cartography better predicts how children learn words compared to closeness centrality. Our results highlight the importance of distance entropy for gaining insights from distance patterns in complex networks. View Full-Text
Keywords: complex networks; network measures; entropy; closeness centrality; multiplex lexical networks complex networks; network measures; entropy; closeness centrality; multiplex lexical networks

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Stella, M.; De Domenico, M. Distance Entropy Cartography Characterises Centrality in Complex Networks. Entropy 2018, 20, 268.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top