This work stems from the idea of describing the scientific productivity of Italian statisticians. There are several problems that must be addressed in achieving this goal: what data should be used? Have the data been cleaned? What techniques can be used? We propose the use of multiple sources and multiple metrics to get a complete information base.We check the correctness of the data using multivariate outlier identification techniques. We appropriately transform the data.We apply robust clustering to verify the existence of homogeneous groups. We suggest the use of forward search to establish a ranking among scholars. The proposed methodology, which, in this case, allowed us to group scholars into four homogeneous groups and sort them according to multidimensional data, can be applied to other similar applications in bibliometrics

Robust analysis of bibliometric data / F. De Battisti, S. Salini. - In: STATISTICAL METHODS & APPLICATIONS. - ISSN 1618-2510. - 22:2(2013), pp. 269-283. [Epub ahead of print] [10.1007/s10260-012-0217-0]

Robust analysis of bibliometric data

F. De Battisti
Primo
;
S. Salini
Ultimo
2013

Abstract

This work stems from the idea of describing the scientific productivity of Italian statisticians. There are several problems that must be addressed in achieving this goal: what data should be used? Have the data been cleaned? What techniques can be used? We propose the use of multiple sources and multiple metrics to get a complete information base.We check the correctness of the data using multivariate outlier identification techniques. We appropriately transform the data.We apply robust clustering to verify the existence of homogeneous groups. We suggest the use of forward search to establish a ranking among scholars. The proposed methodology, which, in this case, allowed us to group scholars into four homogeneous groups and sort them according to multidimensional data, can be applied to other similar applications in bibliometrics
Bibliometric indicators; Cluster analysis; Forward search; Multivariate transformation
Settore SECS-S/01 - Statistica
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/209646
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