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Thirty-six years of contributions to queueing systems: a content analysis, topic modeling, and graph-based exploration of research published in the QUESTA journal

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  • Aminath Shausan

    (The University of Queensland)

  • Aapeli Vuorinen

    (Columbia University)

Abstract

We investigate the 36-year history of research published in the journal Queueing Systems: Theory and Applications (QUESTA), to uncover trends over time in the research topics and themes covered as well as in authorship, co-authorship, and institutional affiliation. Our analysis includes three different approaches. First, we conduct a content analysis of titles and abstracts using selected keywords to examine trends in the three themes of models, methods, and concepts applied in each article. Second, we employ unsupervised topic modeling to identify more hidden topics discussed in the journal. Finally, we analyze the co-authorship graph to identify trends in co-authorship and changes in collaboration practices between authors and their research institutions. Our findings reveal a persistent popularity of studies focused on the basic modeling of queues, queueing networks, and queueing systems. We also confirm an increase in collaboration among authors over time.

Suggested Citation

  • Aminath Shausan & Aapeli Vuorinen, 2023. "Thirty-six years of contributions to queueing systems: a content analysis, topic modeling, and graph-based exploration of research published in the QUESTA journal," Queueing Systems: Theory and Applications, Springer, vol. 104(1), pages 3-18, June.
    • Handle: RePEc:spr:queues:v:104:y:2023:i:1:d:10.1007_s11134-023-09876-w
    DOI: 10.1007/s11134-023-09876-w
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    References listed on IDEAS

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    1. Jiang, Hanchen & Qiang, Maoshan & Lin, Peng, 2016. "A topic modeling based bibliometric exploration of hydropower research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 226-237.
    2. Chyi-Kwei Yau & Alan Porter & Nils Newman & Arho Suominen, 2014. "Clustering scientific documents with topic modeling," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(3), pages 767-786, September.
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