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Towards all-author co-citation analysis

机译:进行全作者共引分析

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The present study examines one of the fundamental aspects of author co-citation analysis (ACA): the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting: on the one hand, the traditional type that only counts the first one among a cited work's authors, and on the other hand, a simplified approach to all-author co-citation counting that takes into account the first five authors of a cited work. Results indicate that the picture produced through this simplified all-author co-citation counting contains author groups that are more coherent, and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed. Variations of counting more than first authors are compared. (c) 2006 Elsevier Ltd. All rights reserved.
机译:本研究检查了作者共同引用分析(ACA)的基本方面之一:定义共同引用计数的方式。共引用计数提供了所有后续统计分析和映射所基于的数据,并且我们基于两种不同类型的共引用计数比较ACA结果:一方面,传统类型仅对第一个进行计数被引用作品的作者,另一方面,一种简化的全作者共被引计数方法则考虑了被引用作品的前五位作者。结果表明,通过这种简化的全作者共同引用计数产生的图片包含更加连贯的作者群体,因此更加清晰。但是,与选择和分析相同数量的排名第一的作者时相比,这种图片代表的研究领域的专业数量要少于通过传统的第一作者共同引用计数产生的专业数量。讨论了产生这些影响的原因。比较计数多于第一作者的差异。 (c)2006 Elsevier Ltd.保留所有权利。

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