A practical approach to constructing triple-blind review process with maximal anonymity and fairness

Jisoo Jung; Joo Im Kim; Ji Won Yoon

doi:10.1007/978-3-319-56549-1_17

A practical approach to constructing triple-blind review process with maximal anonymity and fairness

Jisoo Jung, Joo Im Kim, Ji Won Yoon

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Most journals and conferences adopt blind review process to ensure fairness through anonymization. Although the identity of an author is blinded in a manuscript, information about the author is known to the system when an account is created for submission. So, Information leak or the abuse from journal editor, who is able to access this information, could discredit the review process. Therefore, the triple-blind review process has been proposed to maximize anonymity through blinding the author, reviewer and also the editor. However, it has not been widely used compared to single- and double-blind review processes because there is difficulty in selecting the reviewers when the author is not known to the editor. In this paper, we propose a novel scheme to select the adequate reviewers in the triple-blind review process without any disclosure of author information to even the editor. This is done by using machine learning classification and a conflict of interest measuring method.

Original language	English
Title of host publication	Information Security Applications - 17th International Workshop, WISA 2016, Revised Selected Papers
Publisher	Springer Verlag
Pages	198-209
Number of pages	12
Volume	10144 LNCS
ISBN (Print)	9783319565484
DOIs	https://doi.org/10.1007/978-3-319-56549-1_17
Publication status	Published - 2017
Event	17th International Workshop on Information Security Applications, WISA 2016 - Jeju Island, Korea, Republic of Duration: 2016 Aug 25 → 2016 Aug 25

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10144 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	17th International Workshop on Information Security Applications, WISA 2016
Country/Territory	Korea, Republic of
City	Jeju Island
Period	16/8/25 → 16/8/25

Keywords

Artificial neural network
Author identification
Blind review process
Conflict Of Interest
Multinomial naive Bayes

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-56549-1_17

Cite this

Jung, J., Kim, J. I., & Yoon, J. W. (2017). A practical approach to constructing triple-blind review process with maximal anonymity and fairness. In Information Security Applications - 17th International Workshop, WISA 2016, Revised Selected Papers (Vol. 10144 LNCS, pp. 198-209). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10144 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-56549-1_17

A practical approach to constructing triple-blind review process with maximal anonymity and fairness. / Jung, Jisoo; Kim, Joo Im; Yoon, Ji Won.
Information Security Applications - 17th International Workshop, WISA 2016, Revised Selected Papers. Vol. 10144 LNCS Springer Verlag, 2017. p. 198-209 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10144 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jung, J, Kim, JI & Yoon, JW 2017, A practical approach to constructing triple-blind review process with maximal anonymity and fairness. in Information Security Applications - 17th International Workshop, WISA 2016, Revised Selected Papers. vol. 10144 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10144 LNCS, Springer Verlag, pp. 198-209, 17th International Workshop on Information Security Applications, WISA 2016, Jeju Island, Korea, Republic of, 16/8/25. https://doi.org/10.1007/978-3-319-56549-1_17

Jung J, Kim JI, Yoon JW. A practical approach to constructing triple-blind review process with maximal anonymity and fairness. In Information Security Applications - 17th International Workshop, WISA 2016, Revised Selected Papers. Vol. 10144 LNCS. Springer Verlag. 2017. p. 198-209. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-56549-1_17

Jung, Jisoo ; Kim, Joo Im ; Yoon, Ji Won. / A practical approach to constructing triple-blind review process with maximal anonymity and fairness. Information Security Applications - 17th International Workshop, WISA 2016, Revised Selected Papers. Vol. 10144 LNCS Springer Verlag, 2017. pp. 198-209 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Most journals and conferences adopt blind review process to ensure fairness through anonymization. Although the identity of an author is blinded in a manuscript, information about the author is known to the system when an account is created for submission. So, Information leak or the abuse from journal editor, who is able to access this information, could discredit the review process. Therefore, the triple-blind review process has been proposed to maximize anonymity through blinding the author, reviewer and also the editor. However, it has not been widely used compared to single- and double-blind review processes because there is difficulty in selecting the reviewers when the author is not known to the editor. In this paper, we propose a novel scheme to select the adequate reviewers in the triple-blind review process without any disclosure of author information to even the editor. This is done by using machine learning classification and a conflict of interest measuring method.",

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A practical approach to constructing triple-blind review process with maximal anonymity and fairness

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Keywords

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