Developing a model for individual-level measurement of research activity and citation impact

Abstract

In the present study, we develop and apply a model for individual-level evaluation of research activity and citation impact. In particular, we analyse publication activity and citation impact on the basis of a unique cleaned national dataset, where the most commonly known issue in individual-level bibliometrics, namely the problem with large-scale author identification is eliminated. The full individual validation of the set also helps gain clarity regarding the final limitations of the subject, profile and seniority factor in productivity studies. The study focuses on the following questions. Firstly, can we extend the model of Characteristic Scores and Scales (CSS) to publication activity and what are the caveats? Secondly, in how far does co-authorship fractionation matter affect the indictors? Finally, how can we combine publication and citation CSS models? In order to answer these questions, a 10-year publication dataset of the Norwegian Cristin database was used in combination with citations from the Clarivate Analytics Web of Science Core Collection.