A1 Journal article (refereed)
Can we automate expert-based journal rankings? : analysis of the Finnish publication indicator (2020)

Saarela, M., & Kärkkäinen, T. (2020). Can we automate expert-based journal rankings? : analysis of the Finnish publication indicator. Journal of Informetrics, 14(2), Article 101008. https://doi.org/10.1016/j.joi.2020.101008

JYU authors or editors

Publication details

All authors or editors: Saarela, Mirka; Kärkkäinen, Tommi

Journal or series: Journal of Informetrics

ISSN: 1751-1577

eISSN: 1875-5879

Publication year: 2020

Volume: 14

Issue number: 2

Article number: 101008

Publisher: Elsevier

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1016/j.joi.2020.101008

Publication open access: Not open

Publication channel open access:

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/67782

Abstract

The publication indicator of the Finnish research funding system is based on a manual ranking of scholarly publication channels. These ranks, which represent the evaluated quality of the channels, are continuously kept up to date and thoroughly reevaluated every four years by groups of nominated scholars belonging to different disciplinary panels. This expert-based decision-making process is informed by available citation-based metrics and other relevant metadata characterizing the publication channels. The purpose of this paper is to introduce various approaches that can explain the basis and evolution of the quality of publication channels, i.e., ranks. This is important for the academic community, whose research work is being governed using the system. Data-based models that, with sufficient accuracy, explain the level of or changes in ranks provide assistance to the panels in their multi-objective decision making, thus suggesting and supporting the need to use more cost-effective, automated ranking mechanisms. The analysis relies on novel advances in machine learning systems for classification and predictive analysis, with special emphasis on local and global feature importance techniques.

Keywords: science publishing; publications; scientific journals; evaluation; ranking lists; research financing; automation; machine learning

Free keywords: performance-based research funding system; machine learning; automation; feature importance

Contributing organizations

Related projects

Ministry reporting: Yes

Reporting Year: 2020

JUFO rating: 3