Evidence map›Paper›PMID 33746310›Full record

ArticleScientometrics2020

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

Sitaram Devarakonda, Dmitriy Korobskiy, Tandy Warnow, George Chacko

Abstract read
In one paragraph

Article in Scientometrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Citation analysis of computer systems papers.PeerJ. Computer science · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sitaram DevarakondaNetelabs, NET ESolutions Corporation, McLean, VA.
Dmitriy KorobskiyNetelabs, NET ESolutions Corporation, McLean, VA.
Tandy WarnowDept of Computer Science, University of Illinois Urbana-Champaign, Champaign IL.
George ChackoNetelabs, NET ESolutions Corporation, McLean, VA.

Funding

NIDA NIH HHS HHSN271201700053CNIDA NIH HHS HHSN271201800040C
6 · The paper itself

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 (ASJC). 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.

Indexed as

01A8501A90BibliometricsClusteringComputer ScienceDBLPResearch Evaluation

Identifiers

PMID33746310
PMCPMC7968068

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.