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The Role of Google Scholar in Evidence Reviews and Its Applicability to Grey Literature Searching

机译:Google学术搜索在证据审核中的作用及其在灰色文献搜索中的适用性

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摘要

Google Scholar (GS), a commonly used web-based academic search engine, catalogues between 2 and 100 million records of both academic and grey literature (articles not formally published by commercial academic publishers). Google Scholar collates results from across the internet and is free to use. As a result it has received considerable attention as a method for searching for literature, particularly in searches for grey literature, as required by systematic reviews. The reliance on GS as a standalone resource has been greatly debated, however, and its efficacy in grey literature searching has not yet been investigated. Using systematic review case studies from environmental science, we investigated the utility of GS in systematic reviews and in searches for grey literature. Our findings show that GS results contain moderate amounts of grey literature, with the majority found on average at page 80. We also found that, when searched for specifically, the majority of literature identified using Web of Science was also found using GS. However, our findings showed moderate/poor overlap in results when similar search strings were used in Web of Science and GS (10–67%), and that GS missed some important literature in five of six case studies. Furthermore, a general GS search failed to find any grey literature from a case study that involved manual searching of organisations’ websites. If used in systematic reviews for grey literature, we recommend that searches of article titles focus on the first 200 to 300 results. We conclude that whilst Google Scholar can find much grey literature and specific, known studies, it should not be used alone for systematic review searches. Rather, it forms a powerful addition to other traditional search methods. In addition, we advocate the use of tools to transparently document and catalogue GS search results to maintain high levels of transparency and the ability to be updated, critical to systematic reviews.
机译:Google Scholar(GS)是一种常用的基于Web的学术搜索引擎,它对2亿至1亿条学术和灰色文献(商业学术出版商未正式发布的文献)记录进行分类。 Google学术搜索可整理整个互联网上的结果,并且可以免费使用。结果,作为系统综述所要求的搜索文献的方法,特别是在搜索灰色文献的方法中,它受到了极大的关注。对GS作为独立资源的依赖已经引起了很大的争论,但是,尚未研究其在灰色文献搜索中的功效。使用来自环境科学的系统评价案例研究,我们研究了GS在系统评价和灰色文献搜索中的效用。我们的研究结果表明,GS的结果包含适量的灰色文献,大多数平均在第80页上找到。我们还发现,当进行特定搜索时,使用Web of Science鉴定的大多数文献也都是使用GS发现的。但是,我们的发现显示,在Web of Science和GS中使用相似的搜索字符串时,结果存在中等/较差的重叠(10-67%),并且在六个案例研究中的五个中,GS错过了一些重要的文献。此外,一般的GS搜​​索无法从涉及手动搜索组织网站的案例研究中找到任何灰色文献。如果用于灰色文献的系统评价,我们建议对文章标题的搜索应集中在前200至300个结果上。我们得出的结论是,尽管Google学术搜索可以找到许多灰色文献和特定的已知研究,但不应单独将其用于系统的评论搜索。相反,它是其他传统搜索方法的有力补充。此外,我们提倡使用工具透明地记录和分类GS搜索结果,以保持较高的透明度和更新能力,这对系统评价至关重要。

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