Bibliometric analysis of CiteSeer data for countries

Bibliometric analysis of CiteSeer data for countries

This article describes the results of our analysis of the data from the CiteSeer digital library.First, we examined the data from the point of view of source top-level Internet domainsfrom which the data were collected. Second, we measured country shares in publicationsindexed by CiteSeer and compared them to those based on mainstream bibliographic datafrom the Web of Science and Scopus. And third, we concentrated on analyzing publicationsand their citations aggregated by countries. This way, we generated rankings of the mostinfluential countries in computer science using several non-recursive as well as recursivemethods such as citation counts or PageRank. We conclude that even if East Asian countriesare underrepresented in CiteSeer, its data may well be used along with other conventionalbibliographic databases for comparing the computer science research productivity and performanceof countries.
The available full text is a preprint of the article.

Keywords: CiteSeer, CiteSeerX, Citations, Shares, Countries, Internet domains.

Year: 2012

Journal ISSN: 0306-4573
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Authors of this publication:


Dalibor Fiala


E-mail: dalfia@kiv.zcu.cz
WWW: http://www.kiv.zcu.cz/~dalfia/

Dalibor is an associate professor at the Department of Computer Science and Engineering at the University of West Bohemia in Pilsen, Czech Republic. He is interested in web mining, information retrieval, and information science.

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Social Networks Analysis

Authors:  Karel Je┼żek, Dalibor Fiala, Michal Nykl
Desc.:Application of PageRank algorithm and its modifications on exploration of network structures, particularly citation and coautorship networks.