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Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks

机译:科学合作与认可:共同作者和引文网络的网络分析

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摘要

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.
机译:科学合作和认可是公认的研究主题,它利用三种方法:调查/问卷调查,文献计量和复杂网络分析。本文将主题建模和寻路算法相结合,以确定生产性作者是否倾向于与具有相同或不同兴趣的研究人员进行协作或相互引用,以及被高引用的作者是否倾向于进行协作或相互引用。结果表明,以信息检索为测试领域,富有成果的作者倾向于直接与具有相同研究兴趣的同事共同撰写并密切引用他们。他们通常不直接与具有不同研究主题的同事合作,而是直接或间接引用他们;与被高引用的作者通常不会互相合着书,而是互相引用。

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