6533b86efe1ef96bd12cb660
RESEARCH PRODUCT
Can we automate expert-based journal rankings? Analysis of the Finnish publication indicator
Tommi KärkkäinenMirka Saarelasubject
tiedelehdetfeature importanceComputer scienceProcess (engineering)rankinglistatjulkaisutmedia_common.quotation_subjectLibrary and Information Sciences050905 science studiestutkimusrahoitusautomaatioperformance-based research funding systemFeature (machine learning)Quality (business)automationmedia_commonbusiness.industry05 social sciencesData scienceAutomationComputer Science ApplicationsMetadatamachine learningkoneoppiminenRanking0509 other social sciences050904 information & library sciencesbusinessCitationarviointiDisciplinetieteellinen julkaisutoimintadescription
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. peerReviewed
year | journal | country | edition | language |
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2020-05-01 | Journal of Informetrics |