A regression analysis of researchers’ social network metrics on their citation performance in a college of engineering
作者：
Highlights：
• Two issues, (1) co-authorship is seen as the partial or rough indicator of scientific collaboration and (2) researchers’ collaboration network can be regarded as a proxy for their communication network, are addressed.
• A data collection method is used to obtain researchers’ both in-progress and completed collaborative outputs.
• The data is collected to analyze researchers’ communication and multiple collaborative output networks.
• A bivariate Poisson regression models are run to test the impact of social network metrics obtained from researchers’ multiple networks on their citation performance (h-index).
摘要
•Two issues, (1) co-authorship is seen as the partial or rough indicator of scientific collaboration and (2) researchers’ collaboration network can be regarded as a proxy for their communication network, are addressed.•A data collection method is used to obtain researchers’ both in-progress and completed collaborative outputs.•The data is collected to analyze researchers’ communication and multiple collaborative output networks.•A bivariate Poisson regression models are run to test the impact of social network metrics obtained from researchers’ multiple networks on their citation performance (h-index).
论文关键词：Collaborative networks,Social network analysis,Poisson regression,Self-reported data,Citation-based research performance
论文评审过程：Received 10 March 2014, Revised 4 June 2014, Accepted 5 June 2014, Available online 28 June 2014.
论文官网地址：https://doi.org/10.1016/j.joi.2014.06.004
