Academic Ranking with Web Mining and Axiomatic Analysis
Abstract
Academic ranking is a public topic, such as for universities, colleges, or departments, which has significant educational, administrative and social effects. Popular ranking systems include the US News & World Report (USNWR), the Academic Ranking of World Universities (ARWU), and others. The most popular observables for such ranking are academic publications and their citations. However, a rigorous, quantitative and thorough methodology has been missing for this purpose. With modern web technology and axiomatic bibliometric analysis, here we perform a feasibility study on Microsoft Academic Search metadata and obtain the first-of-its-kind ranking results for American departments of computer science. This approach can be extended for fully automatic intuitional and college ranking based on comprehensive data on Internet.
Keywords
Cite
@article{arxiv.1301.1563,
title = {Academic Ranking with Web Mining and Axiomatic Analysis},
author = {Kun Tang and Qiwei Jin and Xin Zou and Jiansheng Yang and Michael Vannier and Ge Wang},
journal= {arXiv preprint arXiv:1301.1563},
year = {2013}
}
Comments
11 pages, 3 figures, 3 tables, and 10 references