Author ranking based on personalized PageRank
Michal Campr and
Journal of Informetrics, 2015, vol. 9, issue 4, 777-799
In this paper we evaluate citation networks of authors, publications and journals, constructed from the ISI Web of Science database (Computer Science categories). Our aim was to find a method with which to rank authors of scientific papers so that the most important occupy the top positions. We utilized a hand-made list of authors, each of whom have received an ACM Fellowship or have been awarded by an ACM SIG (Artificial Intelligence or Hardware categories). The developed method also included the adoption of the PageRank algorithm, which can be considered a measure of prestige, as well as other measures of significance (h-index, publication count, citation count, publication's author count), with these measures analyzed regarding their influence on the final rankings.
Keywords: Citation analysis; Author ranking; PageRank; h-Index; Impact Factor; ISI Web of Science (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:9:y:2015:i:4:p:777-799
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