Viewing computer science through citation analysis: Salton and Bergmark Redux
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Viewing computer science through citation analysis: Salton and Bergmark Redux Sitaram Devarakonda1,2 · Dmitriy Korobskiy1 · Tandy Warnow3 · George Chacko1 Received: 23 December 2019 © Akadémiai Kiadó, Budapest, Hungary 2020
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 crosscategory 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. Keywords Bibliometrics · Clustering · Research evaluation · Computer science · DBLP Mathematics Subject Classification 01A85 · 01A90
* George Chacko [email protected] Sitaram Devarakonda [email protected] Dmitriy Korobskiy [email protected] Tandy Warnow [email protected] 1
Netelabs, NET ESolutions Corporation, McLean, VA, USA
2
Present Address: Randstad USA, Atlanta, GA, USA
3
Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA
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Vol.:(0123456789)
Scientometrics
Introduction Computer science, and its applications, has experienced rapid growth and diversification over the last twenty years. As observed in a 2017 US National Academies Report, “A wide range of jobs in virtually all sectors demand computing skills to an unprecedented extent. And every academic discipline finds itself incorporating computing into its research and educational mission” (National Academies of Sciences, Engineering, and Medicine, et al. 2018). More recently, the collective influence of the Internet of Things (IoT), ‘big’ data, accessible cloud computing, and advances in artificial intelligence have been presented as a driver for digital transformation (Siebel 2019). Given this rapid growth and expansion, an updated understanding of the present state and structure of computer science and its relationship to other fields can inform planning and policy making at multiple levels from national level funding all the way down to faculty hiring strategy. In historical precedent, Salton and Bergmark conducted a study in 1979 of the computer science literature (419 computer articles published in 1974, and 3812 references cited in these articles) (Salton and Bergmark 1979). Noting that that the scientific literature serves a rich source of information to study the structure and historical development of a field, these authors described the glob
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