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Improving Co-authorship Network Structures by Combining Heterogeneous Data Sources

Authors :
Vittorio Fuccella
Maria Prosperina Vitale
Domenico De Stefano
Susanna Zaccarin
Di Battista, Tonio, Moreno, Elías, Racugno, Walter
Fuccella, Vittorio
DE STEFANO, Domenico
Vitale, Maria Prosperina
Zaccarin, Susanna
Source :
Topics on Methodological and Applied Statistical Inference ISBN: 9783319440927
Publication Year :
2016
Publisher :
Springer International Publishing, 2016.

Abstract

The present paper aims at describing the scientific collaboration patterns of the Italian academic statisticians by merging bibliographic data from heterogenous sources–ISI-WoS, Current Index to Statistics, and the database of nationally funded research projects, PRIN. To obtain a unified database, containing both top international as well as nationally oriented production, information were com- bined by identifying and linking duplicate records, i.e. record linkage. The unique co-authorship network was then used as basis for network analysis.

Details

ISBN :
978-3-319-44092-7
ISBNs :
9783319440927
Database :
OpenAIRE
Journal :
Topics on Methodological and Applied Statistical Inference ISBN: 9783319440927
Accession number :
edsair.doi.dedup.....7e81ae3190973a723bc03fbb23b385f0