Text-Mining Research Group

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

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Dalibor Fiala

Phone: +420 377 63 2429
E-mail: dalfia@kiv.zcu.cz
WWW: http://www.kiv.zcu.cz/~dalfia/

Dalibor is the research group coordinator and 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 data mining, web mining, information retrieval, informetrics, and information science.

Social Networks Analysis
Authors:	Karel Ježek, Dalibor Fiala, Michal Nykl
Desc.:	Application of the PageRank algorithm and its modifications to the exploration of network structures, particularly citation and co-autorship networks.