主题：National and international scientific elites: A comparison between a Chinese bibliometric database and the Web of Science in terms of authors and their performanc
报告人：Fei Shu（舒非） PhD candidate
主持人：李江 教授
时间：2018年4月17日下午3点
地点：best365在线官网登录入口211会议室
报告人简介：
Fei Shu is an ABD (All but dissertation) PhD candidate in the School of Information Studies at McGill University. He also works with Dr. Vincent Larivière at Université de Montréal and Dr. Cassidy Sugimoto at Indiana University in various research projects. His research focuses on the domain of bibliometrics and scholarly communication but also relates to other topics such as academic publishing, information visualization, social media, and science policy. He has published more than 30 peer-reviewed papers including 12 journal articles; his research has been funded by research grants worth more than 100,000 USD; his publications have been disseminated by news media such as MIT Technology Review, Times Higher Education, BBC and Financial Times.
报告摘要：
With the significant development of China’s economy and scientific activity, its scientific publication activity is experiencing a period of rapid growth. However, measuring China’s research output remains a challenge since Chinese scholars may publish their research in either international or national journal, yet no bibliometric database covers both Chinese and English scientific literature. The purpose of this study is to compare Web of Science (WoS) with a Chinese bibliometric database in terms of authors and their performance, demonstrate the extent of the overlap between the two groups of Chinese scientific elites in both international and Chinese bibliometric databases, and determine how different disciplines may affect this overlap. The results of this study indicate that Chinese bibliometric databases, or a combination of WoS and Chinese bibliometric databases, should be used to evaluate Chinese research performance except in few disciplines in which Chinese research performance could be assessed using WoS only.