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Where should I publish? Heterogeneous, networks-based prediction of paper’s citation success

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  • Klemiński, Rajmund
  • Kazienko, Przemyslaw
  • Kajdanowicz, Tomasz

Abstract

Scientific output, as measured in research published annually, has seen a consistent growth for decades now. As more manuscripts are submitted for publication each year, new publishing venues appear – often as increasingly specialised offshoots of existing journals and conferences. This situation presents scholars with a wealth of publishing venues to consider and choose from for their manuscripts. Surprisingly, we find that the most cited papers are not necessarily found in the highest-ranked journals, while the best conferences dominate in this regard. We find it intriguing that popular Computer Science conferences act like a vacuum of attention, centralising all good publications, while journals are carried less by their renown and thus can attract strong manuscripts even at a low rank. But to what extent does a venue imply a paper’s recognition and popularity?

Suggested Citation

  • Klemiński, Rajmund & Kazienko, Przemyslaw & Kajdanowicz, Tomasz, 2021. "Where should I publish? Heterogeneous, networks-based prediction of paper’s citation success," Journal of Informetrics, Elsevier, vol. 15(3).
    • Handle: RePEc:eee:infome:v:15:y:2021:i:3:s1751157721000717
    DOI: 10.1016/j.joi.2021.101200
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    3. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.

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