Comparative analysis of centrality measures for identifying key agents in the network of regional marketing communities

<p>The article presents a comparative analysis of basic centrality measures (degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, PageRank, and Katz centrality) to identify influential agents in the network of regional marketing communities. The study is based on data from marketing communities in Arkhangelsk, collected through the API of the «VKontakte» platform. The analysis revealed that the network has a pronounced cluster structure and contains hub nodes that ensure its connectivity. Based on the centrality distributions, an assessment of the resilience of the marketing community network was conducted, identifying groups of key nodes that play a significant role in information dissemination.</p>

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Publication Details

Journal
Modelling and Data Analysis
Published
2025-06-30
DOI
https://doi.org/10.17759/mda.2025150201
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparative analysis of centrality measures for identifying key agents in the network of regional marketing communities

А.В. Антонов, R. S. Stirmanova
Modelling and Data Analysis
Digital Marketing and Social Media
article

Comparative analysis of centrality measures for identifying key agents in the network of regional marketing communities

А.В. Антонов, R. S. Stirmanova
article en

Abstract

<p>The article presents a comparative analysis of basic centrality measures (degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, PageRank, and Katz centrality) to identify influential agents in the network of regional marketing communities. The study is based on data from marketing communities in Arkhangelsk, collected through the API of the «VKontakte» platform. The analysis revealed that the network has a pronounced cluster structure and contains hub nodes that ensure its connectivity. Based on the centrality distributions, an assessment of the resilience of the marketing community network was conducted, identifying groups of key nodes that play a significant role in information dissemination.</p>

Modelling and Data AnalysisVol. 15(2)
Northern (Arctic) Federal University (RU)
Openalex Percentile: Top 76%
Digital Marketing and Social Media
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