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Related Experiment Video

Updated: Jun 30, 2026

Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes
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Identifying key papers within a journal via network centrality measures.

Saikou Y Diallo1, Christopher J Lynch1, Ross Gore1

  • 1Virginia Modeling Analysis and Simulation Center, Old Dominion University, 1030 University Boulevard, Suffolk, VA 23435 USA.

Scientometrics
|March 28, 2020
PubMed
Summary

Eigenvector centrality effectively identifies important papers within journals, acting as both a filter and a metric. Other centrality measures like closeness and betweenness show limitations depending on journal focus.

Keywords:
Article-level metricsNetwork centrality analysisPaper filtering

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Area of Science:

  • Bibliometrics
  • Network Science
  • Scholarly Communication

Background:

  • Identifying influential research papers is crucial for navigating scientific literature.
  • Network centrality measures are potential tools for assessing paper importance.

Purpose of the Study:

  • To evaluate network centrality measures (closeness, betweenness, eigenvector) as filters and article-level metrics within journals.
  • To determine the effectiveness of these measures in identifying key publications and their relative importance.

Main Methods:

  • Constructed co-citation networks for papers published in the Public Library of Science (PLOS).
  • Calculated closeness, betweenness, and eigenvector centrality for each paper.
  • Analyzed the scale-free nature of the paper network.

Main Results:

  • Eigenvector centrality proved effective as both a filter and an article-level metric, correlating well with citation counts.
  • Closeness centrality was a poor filter due to a narrow citation range for articles.
  • Betweenness centrality's effectiveness varied: poor for narrow-focus journals, good for multidisciplinary journals identifying paper communities.

Conclusions:

  • Eigenvector centrality is a valuable tool for identifying important papers within journals.
  • The utility of betweenness centrality depends on the journal's scope, being more effective in multidisciplinary settings.