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Hidden connections: Network effects on editorial decisions in four computer science journals

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  • Bravo, Giangiacomo
  • Farjam, Mike
  • Grimaldo Moreno, Francisco
  • Birukou, Aliaksandr
  • Squazzoni, Flaminio

Abstract

This paper aims to examine the influence of authors’ reputation on editorial bias in scholarly journals. By looking at eight years of editorial decisions in four computer science journals, including 7179 observations on 2913 submissions, we reconstructed author/referee-submission networks. For each submission, we looked at reviewer scores and estimated the reputation of submission authors by means of their network degree. By training a Bayesian network, we estimated the potential effect of scientist reputation on editorial decisions. Results showed that more reputed authors were less likely to be rejected by editors when they submitted papers receiving negative reviews. Although these four journals were comparable for scope and areas, we found certain journal specificities in their editorial process. Our findings suggest ways to examine the editorial process in relatively similar journals without recurring to in-depth individual data, which are rarely available from scholarly journals.

Suggested Citation

  • Bravo, Giangiacomo & Farjam, Mike & Grimaldo Moreno, Francisco & Birukou, Aliaksandr & Squazzoni, Flaminio, 2018. "Hidden connections: Network effects on editorial decisions in four computer science journals," Journal of Informetrics, Elsevier, vol. 12(1), pages 101-112.
  • Handle: RePEc:eee:infome:v:12:y:2018:i:1:p:101-112
    DOI: 10.1016/j.joi.2017.12.002
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    3. Petersen, Alexander M., 2019. "Megajournal mismanagement: Manuscript decision bias and anomalous editor activity at PLOS ONE," Journal of Informetrics, Elsevier, vol. 13(4).
    4. Zhang, Guangyao & Xu, Shenmeng & Sun, Yao & Jiang, Chunlin & Wang, Xianwen, 2022. "Understanding the peer review endeavor in scientific publishing," Journal of Informetrics, Elsevier, vol. 16(2).
    5. Federico Bianchi & Francisco Grimaldo & Giangiacomo Bravo & Flaminio Squazzoni, 2018. "The peer review game: an agent-based model of scientists facing resource constraints and institutional pressures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1401-1420, September.
    6. Bianchi, Federico & Grimaldo, Francisco & Squazzoni, Flaminio, 2019. "The F3-index. Valuing reviewers for scholarly journals," Journal of Informetrics, Elsevier, vol. 13(1), pages 78-86.
    7. Kyle Siler & Philippe Vincent-Lamarre & Cassidy R Sugimoto & Vincent Larivière, 2022. "Cumulative advantage and citation performance of repeat authors in scholarly journals," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-17, April.
    8. Pilar Valderrama & Evaristo Jiménez-Contreras & Manuel Escabias & Mariano J. Valderrama, 2022. "Introducing a bibliometric index based on factor analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 509-522, January.
    9. Mengyi Sun & Jainabou Barry Danfa & Misha Teplitskiy, 2022. "Does double‐blind peer review reduce bias? Evidence from a top computer science conference," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(6), pages 811-819, June.

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