Exploring the Effects of Data Set Choice on Measuring International Research Collaboration: an Example Using the ACM Digital Library and Microsoft Academic Graph
Digital Libraries
2019-05-31 v1 Social and Information Networks
Abstract
International research collaboration (IRC) measurement is important because countries can and want to benefit from international collaboration but performing the same measurement procedure on different data sets can lead to different results. This study aims to explore the effects of data set choice on IRC measurement.
Keywords
Cite
@article{arxiv.1905.12834,
title = {Exploring the Effects of Data Set Choice on Measuring International Research Collaboration: an Example Using the ACM Digital Library and Microsoft Academic Graph},
author = {Ba Xuan Nguyen and Markus Luczak-Roesch and Jesse David Dinneen},
journal= {arXiv preprint arXiv:1905.12834},
year = {2019}
}
Comments
This paper was accepted for publication at the 17th INTERNATIONAL CONFERENCE ON SCIENTOMETRICS & INFORMETRICS (ISSI 2019)