Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks.
Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks.
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DOI：
10.1016/j.joi.2010.10.008
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发表时间：
2011-01-01
影响因子：
3.7
通讯作者：
Ding Y
中科院分区：
文献类型：
--
作者：
Ding Y
科学合作与认可是一个成熟的研究课题，主要采用三种方法：调查/问卷、文献计量学和复杂网络分析。本文结合了主题建模和路径查找算法，以确定是否生产的作者倾向于合作或引用研究人员相同或不同的利益，以及是否高引用作者倾向于合作或相互引用。结果表明，多产作者倾向于与研究兴趣相同的同行直接合著，并密切引用;多产作者一般不与研究主题不同的同行直接合作，而是直接或间接引用;高被引作者一般不与其他同行合著，而是密切引用。
Scientific collaboration and endorsement are well-established research topics which utilize three kinds of methods: survey/questionnaire, bibliometrics, and complex network analysis. This paper combines topic modeling and path-finding algorithms to determine whether productive authors tend to collaborate with or cite researchers with the same or different interests, and whether highly cited authors tend to collaborate with or cite each other. Taking information retrieval as a test field, the results show that productive authors tend to directly coauthor with and closely cite colleagues sharing the same research interests; they do not generally collaborate directly with colleagues having different research topics, but instead directly or indirectly cite them; and highly cited authors do not generally coauthor with each other, but closely cite each other.