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Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix

Interactions between countries originate from diverse aspects such as geographic proximity, trade, socio-cultural habits, language, religions, etc. Geopolitics studies the influence of a country’s geographic space on its political power and its relationships with other countries. This work reveals t...

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Detalles Bibliográficos
Autores principales: El Zant, Samer, Jaffrès-Runser, Katia, Shepelyansky, Dima L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108488/
https://www.ncbi.nlm.nih.gov/pubmed/30142201
http://dx.doi.org/10.1371/journal.pone.0201397
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author El Zant, Samer
Jaffrès-Runser, Katia
Shepelyansky, Dima L.
author_facet El Zant, Samer
Jaffrès-Runser, Katia
Shepelyansky, Dima L.
author_sort El Zant, Samer
collection PubMed
description Interactions between countries originate from diverse aspects such as geographic proximity, trade, socio-cultural habits, language, religions, etc. Geopolitics studies the influence of a country’s geographic space on its political power and its relationships with other countries. This work reveals the potential of Wikipedia mining for geopolitical study. Actually, Wikipedia offers solid knowledge and strong correlations among countries by linking web pages together for different types of information (e.g. economical, historical, political, and many others). The major finding of this paper is to show that meaningful results on the influence of country ties can be extracted from the hyperlinked structure of Wikipedia. We leverage a novel stochastic matrix representation of Markov chains of complex directed networks called the reduced Google matrix theory. For a selected small size set of nodes, the reduced Google matrix concentrates direct and indirect links of the million-node sized Wikipedia network into a small Perron-Frobenius matrix keeping the PageRank probabilities of the global Wikipedia network. We perform a novel sensitivity analysis that leverages this reduced Google matrix to characterize the influence of relationships between countries from the global network. We apply this analysis to two chosen sets of countries (i.e. the set of 27 European Union countries and a set of 40 top worldwide countries). We show that with our sensitivity analysis we can exhibit easily very meaningful information on geopolitics from five different Wikipedia editions (English, Arabic, Russian, French and German).
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spelling pubmed-61084882018-09-18 Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix El Zant, Samer Jaffrès-Runser, Katia Shepelyansky, Dima L. PLoS One Research Article Interactions between countries originate from diverse aspects such as geographic proximity, trade, socio-cultural habits, language, religions, etc. Geopolitics studies the influence of a country’s geographic space on its political power and its relationships with other countries. This work reveals the potential of Wikipedia mining for geopolitical study. Actually, Wikipedia offers solid knowledge and strong correlations among countries by linking web pages together for different types of information (e.g. economical, historical, political, and many others). The major finding of this paper is to show that meaningful results on the influence of country ties can be extracted from the hyperlinked structure of Wikipedia. We leverage a novel stochastic matrix representation of Markov chains of complex directed networks called the reduced Google matrix theory. For a selected small size set of nodes, the reduced Google matrix concentrates direct and indirect links of the million-node sized Wikipedia network into a small Perron-Frobenius matrix keeping the PageRank probabilities of the global Wikipedia network. We perform a novel sensitivity analysis that leverages this reduced Google matrix to characterize the influence of relationships between countries from the global network. We apply this analysis to two chosen sets of countries (i.e. the set of 27 European Union countries and a set of 40 top worldwide countries). We show that with our sensitivity analysis we can exhibit easily very meaningful information on geopolitics from five different Wikipedia editions (English, Arabic, Russian, French and German). Public Library of Science 2018-08-24 /pmc/articles/PMC6108488/ /pubmed/30142201 http://dx.doi.org/10.1371/journal.pone.0201397 Text en © 2018 El Zant et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
El Zant, Samer
Jaffrès-Runser, Katia
Shepelyansky, Dima L.
Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
title Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
title_full Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
title_fullStr Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
title_full_unstemmed Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
title_short Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
title_sort capturing the influence of geopolitical ties from wikipedia with reduced google matrix
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108488/
https://www.ncbi.nlm.nih.gov/pubmed/30142201
http://dx.doi.org/10.1371/journal.pone.0201397
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