首页 | 本学科首页   官方微博 | 高级检索  
     检索      


The use of different data sources in the analysis of co-authorship networks and scientific performance
Authors:Domenico De Stefano  Vittorio Fuccella  Maria Prosperina Vitale  Susanna Zaccarin
Institution:1. Department of Economics, Business, Mathematics and Statistics “B. de Finetti”, University of Trieste, Italy;2. Department of Informatics, University of Salerno, Italy;3. Department of Economics and Statistics, University of Salerno, Italy
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.
Keywords:Bibliometric databases  Co-authorship data  Network topology  Scientific performance  h-Index  GEV model
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号