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Analyzing the Common Wisdom of Binarization Doctrine in Internationality Classification of Journals: A Machine Learning Approach

1, 1★, 2, 2★ Corresponding author

  1. 1Department of computer science and engg, PESIT-BSC, Bangalore-560100 (affiliated to Visvesvarya Technical University, Belagavi), Karnataka, INDIA.
  2. 2Department of Computer Science, IIT Patna, Bihar, INDIA.

CORRESPONDENCE

Sudeepa Roy Dey

Department of computer science and engg, PESIT-BSC, Bangalore-560100 (affiliated to Visvesvarya Technical University, Belagavi), Karnataka, INDIA.

sudeepar@gmail.com

Received: 09-01-2019; Revised: 11-06-2019; Accepted: 16-09-2019.

Volume 8, Issue 2s · pp. s7-s38 · 2019 · DOI: 10.5530/jscires.8.2.22

ABSTRACT

Evaluating and identifying “Internationality” of peer reviewed journals is a hotly debated topic. The problem broadly focuses on whether a journal is international or not, indicating a strong tilt toward binary classification doctrine. The manuscript investigates the doctrine, for the first time. The authors have validated their study further by using minimum error rate classifier, investigated theoretical lower and upper bounds of classification error in the context of internationality. The novel approach has rich ramifications in Scientometrics. Further, we propose a new principle of classification that results in greater accuracy fortifying the assertion.

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    Sampatrao, G. S., Dey, S. R., Bansal, A., & Saha, S. (2019). Analyzing the Common Wisdom of Binarization Doctrine in Internationality Classification of Journals: A Machine Learning Approach. Journal of Scientometric Research, 8(2s), s7-s38. https://doi.org/10.5530/jscires.8.2.22

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    © 2019 Author(s)

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. CC BY-NC-SA 4.0