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Automated citation indexing [43] has changed the nature of citation analysis research, allowing millions of citations to be analyzed for large scale patterns and knowledge discovery. The first example of automated citation indexing was CiteSeer, later to be followed by Google Scholar. More recently, advanced models for a dynamic analysis of ...
Google Scholar puts high weight on citation counts in its ranking algorithm and therefore is being criticized for strengthening the Matthew effect; [30] as highly cited papers appear in top positions they gain more citations while new papers hardly appear in top positions and therefore get less attention by the users of Google Scholar and hence ...
His papers consistently appear in top economics journals and he has more than 10,000 Google Scholar citations, five contributions with more than 1,000 citations and over 35 with more than 100 citations. [4]
The database itself should be the primary source of statistics, and if it is not accessible, the independent estimates released as journal papers should be. Notably, Google Scholar does not offer such detail, but the database's size has been calculated. [2]
Author-level metrics are citation metrics that measure the bibliometric impact of individual authors, researchers, academics, and scholars. Many metrics have been developed that take into account varying numbers of factors (from only considering the total number of citations, to looking at their distribution across papers or journals using statistical or graph-theoretic principles).
Bibliometrics is the application of statistical methods to the study of bibliographic data, especially in scientific and library and information science contexts, and is closely associated with scientometrics (the analysis of scientific metrics and indicators) to the point that both fields largely overlap.
Das has published 350+ journal articles and 475+ peer-reviewed conference papers, gathering 34,300+ citations according to Google Scholar [2] and 50 invited book chapters. He is one of the most prolific authors in computer science according to DBLP [ 3 ] His current h-index is 91.
The version of the index that Ioannidis used Scopus citations instead of Google Scholar citations, since many of the signatories had no Google Scholar pages. [7] The K-index suggests that the number of citations of a given scientist is comparable to their scientific value. This assumption has been criticized. [8] [9]