Abstract

Computer science has experienced dramatic growth and diversification over the last twenty years. Towards a current understanding of the structure of this discipline, we analyze a large sample of the computer science literature from the DBLP database. For insight on the features of this cohort and the relationship within its components, we have constructed article level clusters based on either direct citations or co-citations, and reconciled them with major and minor subject categories in the All Science Journal Classification. We describe complementary insights from clustering by direct citation and co-citation, and both point to the increase in computer science publications and their scope. Our analysis reveals cross-category clusters, some that interact with external fields, such as the biological sciences, while others remain inward looking. Overall, we document an increase in computer science publications and their scope.

Original languageEnglish (US)
Pages (from-to)271-287
Number of pages17
JournalScientometrics
Volume125
Issue number1
DOIs
StatePublished - Oct 1 2020

Keywords

  • Bibliometrics
  • Clustering
  • Computer science
  • DBLP
  • Research evaluation

ASJC Scopus subject areas

  • General Social Sciences
  • Computer Science Applications
  • Library and Information Sciences

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