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 domains from which the data were collected. Second, we measured country shares in publications indexed by CiteSeer and compared them to those based on mainstream bibliographic data from the Web of Science and Scopus. And third, we concentrated on analyzing publications and their citations aggregated by countries. This way, we generated rankings of the most influential countries in computer science using several non-recursive as well as recursive methods such as citation counts or PageRank. We conclude that even if East Asian countries are underrepresented in CiteSeer, its data may well be used along with other conventional bibliographic databases for comparing the computer science research productivity and performance of countries. âº Data from CiteSeer digital library are analyzed. âº Publication country shares are determined and compared. âº Citation rankings of countries are generated.