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The use of different data sources in the analysis of co-authorship networks and scientific performance
- Publication Year :
- 2013
-
Abstract
- Scientific collaboration is usually derived from archival co-authorship data. Several data sources may be examined, but they all have advantages and disadvantages, especially when a specific discipline or community is of interest. The aim of this paper is to explore the effect of the use of three data sources – Web of Science, Current Index to Statistics and nationally funded research projects – on the analysis of co-authorship networks among Italian academic statisticians. Results provide evidence of our hypotheses on distinct collaboration patterns among statisticians, as well as distinct effects of scientist network positions on scientific performance, by both Statistics subfield and data source.
- Subjects :
- Data source
Network topology
Sociology and Political Science
Web of science
Computer science
Bibliometric databases
Co-authorship data
Scientific performance
h-Index
GEV model
General Social Sciences
Data science
Bibliometric databases, Co-authorship data, Network topology, Scientific performance, h-Index, GEV model
Bibliometric database
Index (publishing)
Anthropology
Co authorship
General Psychology
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....4664db59d76e42ab4d862184637aa9ca