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Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence

机译:比较专家调查和引文影响期刊的排名方法:来自人工智能领域的示例

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摘要

The purpose of this study is to: (1) develop a ranking of peer-reviewed Al journals; (2) compare the consistency of journal rankings developed with two dominant ranking techniques, expert surveys and journal impact measures; and (3) investigate the consistency of journal ranking scores assigned by different categories of expert judges. The ranking was constructed based on the survey of 873 active Al researchers who ranked the overall quality of 182 peer-reviewed Al journals. It is concluded that expert surveys and citation impact journal ranking methods cannot be used as substitutes. Instead, they should be used as complementary approaches. The key problem of the expert survey ranking technique is that in their ranking decisions, respondents are strongly influenced by their current research interests. As a result, their scores merely reflect their present research preferences rather than an objective assessment of each journal's quality. In addition, the application of the expert survey method favors journals that publish more articles per year.
机译:这项研究的目的是:(1)建立同行评审的Al期刊的排名; (2)比较使用两种主要的排名技术,专家调查和期刊影响度量得出的期刊排名的一致性; (3)研究不同类别的专家法官分配的期刊排名分数的一致性。该排名是根据对873位活跃的Al研究人员的调查得出的,该研究人员对182种同行评审的Al期刊的整体质量进行了排名。结论是专家调查和引用影响期刊排名方法不能替代。相反,应将它们用作补充方法。专家调查分级技术的关键问题在于,在进行分级决策时,受访者会受到当前研究兴趣的强烈影响。结果,他们的分数仅反映了他们当前的研究偏好,而不是对每本期刊质量的客观评估。此外,专家调查方法的应用有利于每年出版更多文章的期刊。

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