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Viewing Computer Science through Citation Analysis: Salton and Bergmark Redux.

Sitaram Devarakonda¹, Dmitriy Korobskiy¹, Tandy Warnow²

¹Netelabs, NET ESolutions Corporation, McLean, VA.

|March 22, 2021

Summary

Computer science literature has grown significantly, showing increased publications and scope. Analysis of DBLP data reveals diverse research clusters, some connecting with external fields like biological sciences.

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Area of Science:

Computer Science
Bibliometrics
Information Science

Background:

Computer science has undergone substantial growth and diversification in the past two decades.
Understanding the evolving structure of computer science is crucial for researchers and institutions.

Purpose of the Study:

To analyze the structure and evolution of computer science literature.
To identify key clusters and their relationships within the discipline.

Main Methods:

Analysis of a large sample of computer science publications from the DBLP database.
Construction of article-level clusters using direct citation and co-citation analysis.
Reconciliation of clusters with the All Science Journal Classification (ASJC) subject categories.

Keywords:

01A85 01A90 Bibliometrics Clustering Computer Science DBLP Research Evaluation

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Main Results:

Both direct citation and co-citation clustering indicate an expansion in the volume and scope of computer science publications.
Identified cross-category clusters, demonstrating interdisciplinary connections and internal specialization.
Some clusters show significant interaction with external fields, such as biological sciences, while others are more insular.

Conclusions:

The study confirms a notable increase in computer science publications and their broadening scope.
Bibliometric analysis reveals a complex and evolving structure within the discipline.
Interdisciplinary links and internal focus coexist within the dynamic landscape of computer science research.