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SankeyNetwork: A clear and concise visualization tool for bibliometric data.

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Summary
This summary is machine-generated.

This study introduces Sankey diagrams and slope graphs to improve bibliometric analysis, enhancing visualization of author collaborations and research themes. These methods offer clearer insights into research patterns and key contributors.

Keywords:
Bibliometric analysisCo-word occurrenceCountry collaborationGene Expression AnalysisNetworkPerformance sheetSankey diagramSankey-type diagrams as Network [SankeyNetwork]Slope graphs

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Area of Science:

  • Bibliometrics and Scientometrics
  • Information Science
  • Research Evaluation

Background:

  • Traditional bibliometric visualizations like co-word networks have limitations in identifying key contributors and themes.
  • Existing methods often struggle with visual complexity and clarity in representing research landscapes.

Purpose of the Study:

  • To propose a novel framework integrating Sankey diagrams with author collaborations and co-word occurrences.
  • To enhance bibliometric visualization by overcoming limitations of traditional methods.
  • To identify key contributors and emerging research themes more effectively.

Main Methods:

  • Analysis of 2252 articles from the Journal of METHODSX (2020-2024).
  • Integration of Sankey diagrams and slope graphs with bibliometric data.
  • Utilizing a summarized performance sheet and the Following-Leading Clustering Algorithm (FLCA).

Main Results:

  • The United States, Symbiosis International (India), and Fengxiang X Han are identified as prominent entities/authors.
  • "MODEL" emerged as the most frequent keyword.
  • A 2020 article by Wondimagegn Mengist received the highest citation count (370).
  • Slope graphs indicated upward trends in four core elements over four years.

Conclusions:

  • The proposed framework, combining performance sheets, Sankey diagrams, and slope graphs, offers clearer insights and reduced visual complexity.
  • These methods are recommended for future bibliometric analyses to detect research hotspots and evolving patterns.
  • Sankey diagrams effectively enhance traditional bibliometric visualization methods for author collaborations.