Indirect Influence Assessment in the Context of Retail Food Network

Fuad Aleskerov, Natalia Meshcheryakova*, Sergey Shvydun

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

We consider an application of long-range interaction centrality (LRIC) to the problem of the influence assessment in the global retail food network. Firstly, we reconstruct an initial graph into the graph of directed intensities based on individual node’s characteristics and possibility of the group influence. Secondly, we apply different models of the indirect influence estimation based on simple paths and random walks. This approach can help us to estimate node-to-node influence in networks. Finally, we aggregate node-to-node influence into the influence index. The model is applied to the food trade network based on the World International Trade Solution database. The results obtained for the global trade by different product commodities are compared with classical centrality measures.

Original languageEnglish
Title of host publicationNetwork Algorithms, Data Mining, and Applications, NET 2018
EditorsIlya Bychkov, Valery A. Kalyagin, Panos M. Pardalos, Oleg Prokopyev
PublisherSpringer
Pages143-160
Number of pages18
ISBN (Print)9783030371562
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event8th International Conference on Network Analysis, NET 2018 - Moscow, Russian Federation
Duration: 18 May 201819 May 2018

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume315
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

Conference8th International Conference on Network Analysis, NET 2018
Country/TerritoryRussian Federation
CityMoscow
Period18/05/1819/05/18

Keywords

  • Food trade network
  • Influence estimation
  • Network analysis

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