Wikipedia ranking of world universities

@article{Lages2015WikipediaRO,
  title={Wikipedia ranking of world universities},
  author={Jos{\'e} Lages and Antoine Patt and Dima L. Shepelyansky},
  journal={The European Physical Journal B},
  year={2015},
  volume={89},
  pages={1-12}
}
Abstract We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the… 
World influence and interactions of universities from Wikipedia networks
TLDR
It is shown that the new reduced Google matrix algorithm allows to determine interactions between leading universities on a scale of ten centuries and this approach also determines the influence of specific universities on world countries.
Mining the World University Rankings from Wikipedia
Global university rankings have played a growing role in the competition for status which has become one of the important evaluation conditions of higher education quality. At present, the evaluation
Novel version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network using Social Impact
TLDR
This paper proposes a new model for the PageRank, CheiRank and 2DRank algorithm based on the use of clickstream and pageviews data in the google matrix construction based on data from Wikipedia and analysed links between articles from 11 language editions.
Wikipedia mining of hidden links between political leaders
TLDR
It is argued that the reduced Google matrix method can form the mathematical basis for studies in social and political sciences analyzing Leader-Members eXchange (LMX) and allows to recover reliably direct and hidden links among political leaders.
Interactions of pharmaceutical companies with world countries, cancers and rare diseases from Wikipedia network analysis
TLDR
Using the English Wikipedia network of more than 5 million articles, a compact description of interactions between these articles is provided that allows us to determine the friendship networks between them, as well as the PageRank sensitivity of countries to pharmaceutical companies and rare renal diseases.
Measuring the academic reputation through citation networks via PageRank
World Influence of Infectious Diseases from Wikipedia Network Analysis
TLDR
The reduced Google matrix method is used to determine the sensitivity of world countries to specific diseases integrating their influence over all their history including the times of ancient Egyptian mummies, demonstrating that the Wikipedia network analysis provides reliable results.
Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
TLDR
This work reveals the potential of Wikipedia mining for geopolitical study by leveraging a novel stochastic matrix representation of Markov chains of complex directed networks called the reduced Google matrix theory.
Geopolitical interactions from reduced Google matrix analysis of Wikipedia
TLDR
This work reveals the potential of Wikipedia mining for geopolitical study by performing a novel stochastic matrix representation of Markov chains of complex directed networks called the reduced Google matrix theory.
Piping “personalized PageRank” Algorithm from the Analytic Hierarchy Process(AHP) – A Case study
TLDR
This paper ranks the institutions purely based on the output (alumni) instead of mixing input-process-teaching-learning-output model, so that the candidates will arrive their own personalized ranking of institutions without depending on any national or international ranking agencies.
...
...

References

SHOWING 1-10 OF 53 REFERENCES
Time evolution of Wikipedia network ranking
TLDR
It is shown that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts.
Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles
TLDR
It is found that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures through ranking of multilingual Wikipedia articles.
Top 100 historical figures of Wikipedia
TLDR
This short popular note presents overview of results and methods of different groups of the world, determined on the basis of statistical methods and mathematical algorithms like PageRank, CheiRank and 2DRank applied to networks of Wikipedia in up to 24 languages.
Interactions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions
TLDR
Considering historical figures who appear in multiple editions as interactions between cultures, a network of cultures is constructed and the most influential cultures are identified according to this network.
Google matrix of the world trade network
TLDR
The study establishes the existence of two solid state like domains of rich and poor countries which remain stable in time, while the majority of countries are shown to be in a gas like phase with strong rank fluctuations.
Google's PageRank and beyond - the science of search engine rankings
TLDR
Any business seriously interested in improving its rankings in the major search engines can benefit from the clear examples, sample code, and list of resources provided.
Google matrix analysis of directed networks
TLDR
This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency on various examples including World Wide Web, Wikipedia, software architecture, world trade, social and citation networks, brain neural networks, DNA sequences and Ulam networks.
On the internal dynamics of the Shanghai ranking
TLDR
It is proposed that the utility and usability of the ARWU could be greatly improved by replacing the unwanted dynamical effects of the annual re-scaling based on raw scores of the best performers.
Multilevel-statistical reformulation of citation-based university rankings: The Leiden ranking 2011/2012
TLDR
A reformulation of the Leiden Ranking 2011/2012 by means of multilevel regression models showed that only 5% of the PPtop10% total variation is attributable to differences between universities, and it is possible to interpret the significance of differences among universities meaningfully.
On using the Shanghai ranking to assess the research performance of university systems
TLDR
A new look at the Shanghai Jiao Tong Academic Ranking of World Universities to evaluate the performance of whole university systems is taken, with a clear picture emerges: at the aggregate level ARWU seems to be a very reliable one-dimensional scale.
...
...