Stability and Similarity in Networks Based on Topology and Nodes Importance

Fuad Aleskerov, Sergey Shvydun*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

8 Citations (Scopus)

Abstract

We propose a model that evaluates how much a network has changed over time in terms of its structure and a set of central elements. The difference of structure is evaluated in terms of node-to-node influence using known nodes correspondence models. To analyze the changes in nodes centralities we adapt an idea of interval orders to the network theory. Our approach can be used to investigate dynamic changes in temporal networks and to identify suspicious or abnormal effects in terms of the topology and its critical members. We can also transform the stability measure to the similarity measure in order to cluster the network in some homogeneous periods. To test our model, we consider the international migration network from 1970 to 2015 and attempt to analyze main changes in migration patterns.

Original languageEnglish
Title of host publicationComplex Networks and Their Applications VII - Volume 1 Proceedings The 7th International Conference on Complex Networks and their Applications COMPLEX NETWORKS 2018
EditorsRenaud Lambiotte, Luis M. Rocha, Pietro Lió, Hocine Cherifi, Luca Maria Aiello, Chantal Cherifi
PublisherSpringer
Pages94-103
Number of pages10
ISBN (Print)9783030054106
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018 - Cambridge, United Kingdom
Duration: 11 Dec 201813 Dec 2018

Publication series

NameStudies in Computational Intelligence
Volume812
ISSN (Print)1860-949X

Conference

Conference7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018
Country/TerritoryUnited Kingdom
CityCambridge
Period11/12/1813/12/18

Keywords

  • Dynamics
  • Network stability
  • Similarity measure
  • Temporal networks
  • Topology

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