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Indirect Influence Assessment in the Context of Retail Food Network

Conference Paper (2020)
Author(s)

Fuad Aleskerov (V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, National Research University Higher School of Economics (HSE University))

Natalia Meshcheryakova (V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, National Research University Higher School of Economics (HSE University))

Sergey Shvydun (National Research University Higher School of Economics (HSE University), V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1007/978-3-030-37157-9_10 Final published version
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Publication Year
2020
Language
English
Affiliation
External organisation
Pages (from-to)
143-160
Publisher
Springer
ISBN (print)
9783030371562
Event
8th International Conference on Network Analysis, NET 2018 (2018-05-18 - 2018-05-19), Moscow, Russian Federation
Downloads counter
130

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.