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Mining citation information from CiteSeer data

By Dalibor Fiala

Abstract

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

Topics: CiteSeer, citation analysis, rankings, evaluation
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.363.7417
Provided by: CiteSeerX
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