Structures of THE, QS and ARWU Top 100 universities’ websites in different languages and social media accounts: Binary matrix approach

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Vladimir M Moskovkin
Munenge - Sizyoongo
He Zhang
Marina V Sadovski


The aim of the study is to understand how the diversity of university language websites and social networks influence the universities’ reputation in the World University Rankings and how this diversity can be described. Combining the union of sets of university names in Times Higher Education (THE), QS World University Ranking (QS), and Academic Ranking of World Universities (ARWU) 2018, the World’s Top 100 Universities Rankings enabled us to obtain a set of 146 universities. From October 18, 2018, through November 1, 2018, the availability of website versions in different languages and social media applications was checked. The study enabled a 146x15 binary matrix to be built in the first case, and a 146x21 one in the second, with 15 meaning the number of website versions in foreign languages, and 21 standing for respective number of various social media accounts.  The binary matrices were clustered with a view to obtaining dense submatrices consisting of units only. The study shows that approximately 47 percent of the universities surveyed have their websites in more than one language. All the 146 universities have websites in English, those in Chinese coming second and equalling to 21. Most popular social networking sites have been revealed, with over 84 percent of universities having Facebook, Twitter, YouTube and Instagram accounts. On the whole, 18 universities form a dense binary submatrix for 6 social media, including four of the above, as well as LinkedIn and Google+.  The binary matrices are proved to be effective for higher education managers and experts focusing on specific regions and social media. Correlational dependence calculations on comparative analysis of traditional and altmetrics rankings are also performed.


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Moskovkin, V. M., Sizyoongo, M. .-., Zhang, H., & Sadovski, M. V. (2021). Structures of THE, QS and ARWU Top 100 universities’ websites in different languages and social media accounts: Binary matrix approach. Malaysian Journal of Library and Information Science, 26(2), 37–67.


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