Wikipedia Ranking of World Universities 2017 (2018)

Available

Dataset

Licence : CC BY-NC-SA doi:10.25666/DATAOSU-2019-01-10

Data creators : José Lages ^[1] ^[2], Dima Shepelyansky ^[3], Célestin Coquidé ^[1] ^[2]

[1] : Institut UTINAM (UMR 6213) (Université de Franche-Comté)

[2] : Observatoire des Sciences de l'Univers - Terre, Homme, Environnement, Temps, Astronomie (UAR 3245) (Université de Franche-Comté)

[3] : Laboratoire de Physique Théorique (UMR 5152)

Description :

We present Wikipedia Ranking of World Universities (WRWU) based on analysis of networks of 24 Wikipedia editions collected in May 2017. With PageRank and CheiRank algorithms we determine ranking of universities averaged over cultural views of these editions. The comparison with the Shanghai ranking gives overlap of 60% for top 100 universities showing that WRWU gives more significance to their historical development. We show that the new reduced Google matrix algorithm allows to determine interactions between leading universities on a scale of ten centuries. This approach also determines the influence of specific universities on world countries. We also compare different cultural views of Wikipedia editions on significance and influence of universities.

Disciplines :

computer science, information systems (engineering science), humanities, multidisciplinary (humanities), physics, mathematical (physics), cultural studies (social sciences), multidisciplinary sciences

Keywords :

complex networks, directed networks, markovian processes, scale free networks, scientometry, theorical physics, universities, Wikipedia, World Wide Web

General metadata

Data acquisition date : from 1 May 2017 to 31 May 2017

Data acquisition methods :

Derived or compiled data :
Web crawling of Wikipedia editions (May 2017) to retrieve information about universities (year of foundation, location, ...).
Simulation or computational data :
PageRank, CheiRank and 2DRank algorithms have been used to rank articles within each of the 24 Wikipedia language editions (May 2017).
Reduced Google matrix method has been used to infer interaction between articles.

Language : English (eng)

Formats : application/pdf, image/png, image/x-eps, text/csv, text/html

Audience : General, Research, Stakeholder, Policy maker