Abstract
The CiteSeer digital library is a useful source of bibliographic information. It allows for retrieving citations, co-authorships, addresses, and affiliations of authors and publications. In spite of this, it has been relatively rarely used for automated citation analyses. This article describes our findings after extensively mining from the CiteSeer data. We explored citations between authors and determined rankings of influential scientists using various evaluation methods including citation and in-degree counts, HITS, PageRank, and its variations based on both the citation and collaboration graphs. We compare the resulting rankings with lists of computer science award winners and find out that award recipients are almost always ranked high. We conclude that CiteSeer is a valuable, yet not fully appreciated, repository of citation data and is appropriate for testing novel bibliometric methods.
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Acknowledgments
This work (The related software may found at http://textmining.zcu.cz/downloads/sciento.php.) was supported in part by the Ministry of Education of the Czech Republic under Grant 2C06009. Many thanks go to the anonymous reviewers for their useful hints and comments and to Karel Ježek for his support of this project.
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Fiala, D. Mining citation information from CiteSeer data. Scientometrics 86, 553–562 (2011). https://doi.org/10.1007/s11192-010-0326-1
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DOI: https://doi.org/10.1007/s11192-010-0326-1