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Interactions and influence of world painters from the reduced Google matrix of Wikipedia networks

El zant, Samer and Jaffrès-Runser, Katia and Frahm, Klaus and Shepelyansky, Dima Interactions and influence of world painters from the reduced Google matrix of Wikipedia networks. (2018) IEEE Access, 6. 47735-47750. ISSN 2169-3536

(Document in English)

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Official URL: https://doi.org/10.1109/ACCESS.2018.2867327


This study concentrates on extracting painting art history knowledge from the network structure of Wikipedia. Therefore, we construct theoretical networks of webpages representing the hyper-linked structure of articles of 7 Wikipedia language editions. These 7 networks are analyzed to extract the most influential painters in each edition using Google matrix theory. Importance of webpages of over 3000 painters are measured using PageRank algorithm. The most influential painters are enlisted and their ties are studied with the reduced Google matrix analysis. Reduced Google Matrix is a powerful method that captures both direct and hidden interactions between a subset of selected nodes taking into account the indirect links between these nodes via the remaining part of large global network. This method originates from the scattering theory of nuclear and mesoscopic physics and field of quantum chaos. From this study, we show that it is possible to extract from the components of the reduced Google matrix meaningful information on the ties between these painters. For instance, our analysis groups together painters that belong to the same painting movement and shows meaningful ties between painters of different movements. We also determine the influence of painters on world countries using link sensitivity between Wikipedia articles of painters and countries. The reduced Google matrix approach allows to obtain a balanced view of various cultural opinions of Wikipedia language editions. The world countries with the largest number of top painters of selected 7 Wikipedia editions are found to be Italy, France, Russia. We argue that this approach gives meaningful information about art and that it could be a part of extensive network analysis on human knowledge and cultures.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
APR 2015 Call of the University of Toulouse - Région Occitanie - MASTODONS-2017 CNRS - ANR-13-CHR2-0002-06 - ANR-11-IDEX-0002-02 - ANR-10-LABX-0037-NEXT
Deposited On:20 Feb 2019 14:58

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