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
- STRUCTURE PREDICTION OF HYBRID NANOPARTICLES VIA ARTIFICIAL INTELLIGENCE
- Kärkkäinen, Tommi
- Academy of Finland
- Competitive funding to strengthen universities’ research profiles. Profiling actions at the JYU, round 3
- Hämäläinen, Keijo
- Academy of Finland
Ministry reporting: Yes
Reporting Year: 2020
JUFO rating: 3