PageRank variants in the evaluation of citation networks |
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| Institution: | 1. Institute for Education and Information Sciences, IBW, University of Antwerp, Venusstraat 35, Antwerp B-2000, Belgium;2. KU Leuven, Department of Mathematics, Celestijnenlaan 200B, B-3000 Leuven, Belgium;3. Library of Tongji University, Tongji University, Siping Street 1239, Shanghai 200092, China;4. SPRU, School of Business, Management and Economics, University of Sussex, Falmer, Brighton BN1 9SL, UK;5. Institute for Education and Information Sciences, IBW, University of Antwerp, Venusstraat 35, Antwerp B-2000, Belgium;1. Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong;2. Advanced Digital Sciences Center, Illinois at Singapore Pte. Ltd., Singapore;1. Laboratory for Studies of Research and Technology Transfer, Institute for System Analysis and Computer Science (IASI-CNR), National Research Council of Italy, Viale Manzoni 30, 00185 Rome, Italy;2. Department of Engineering and Management, University of Rome “Tor Vergata”, Via del Politecnico 1, 00133 Rome, Italy |
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| Abstract: | This paper explores a possible approach to a research evaluation, by calculating the renown of authors of scientific papers. The evaluation is based on the citation analysis and its results should be close to a human viewpoint. The PageRank algorithm and its modifications were used for the evaluation of various types of citation networks. Our main research question was whether better evaluation results were based directly on an author network or on a publication network. Other issues concerned, for example, the determination of weights in the author network and the distribution of publication scores among their authors. The citation networks were extracted from the computer science domain in the ISI Web of Science database. The influence of self-citations was also explored. To find the best network for a research evaluation, the outputs of PageRank were compared with lists of prestigious awards in computer science such as the Turing and Codd award, ISI Highly Cited and ACM Fellows. Our experiments proved that the best ranking of authors was obtained by using a publication citation network from which self-citations were eliminated, and by distributing the same proportional parts of the publications’ values to their authors. The ranking can be used as a criterion for the financial support of research teams, for identifying leaders of such teams, etc. |
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| Keywords: | PageRank Citation analysis Research evaluation Author ranking ISI Web of Science |
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