Google Scholar's Ranking Algorithm: The Impact of Articles' Age (An Empirical Study)

Beel, Joeran; Gipp, Béla

doi:10.1109/itng.2009.317

Cited by 33 publications

(28 citation statements)

References 9 publications

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“…PubMed uses algorithms based on MeSH terms and reports the most recent articles at the top of the list (which likely have not had adequate time to be appropriately cited). In contrast, research studies on Google Scholar's proprietary algorithms have demonstrated that the number of citations is an important criterion in the initial list of articles and that the date of publication is not an important criterion . In our study, the median publication dates for articles retrieved by Google Scholar searches were earlier than those retrieved from the PubMed database.…”

Section: Discussioncontrasting

confidence: 82%

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Medical literature searches: a comparison of PubMed and Google Scholar

Nourbakhsh

Nugent

Wang

et al. 2012

Health Info Libraries J

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Background: Medical literature searches provide critical information for clinicians. However, the best strategy for identifying relevant high-quality literature is unknown. Objectives: We compared search results using PubMed and Google Scholar on four clinical questions and analysed these results with respect to article relevance and quality. Methods: Abstracts from the first 20 citations for each search were classified into three relevance categories. We used the weighted kappa statistic to analyse reviewer agreement and nonparametric rank tests to compare the number of citations for each article and the corresponding journals' impact factors. Results: Reviewers ranked 67.6% of PubMed articles and 80% of Google Scholar articles as at least possibly relevant (P = 0.116) with high agreement (all kappa P-values < 0.01). Google Scholar articles had a higher median number of citations (34 vs. 1.5, P < 0.0001) and came from higher impact factor journals (5.17 vs. 3.55, P = 0.036). Conclusions: PubMed searches and Google Scholar searches often identify different articles. In this study, Google Scholar articles were more likely to be classified as relevant, had higher numbers of citations and were published in higher impact factor journals. The identification of frequently cited articles using Google Scholar for searches probably has value for initial literature searches.

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Section: Discussioncontrasting

confidence: 82%

“…In our study, Google Scholar searches retrieved category 1, 2 articles with a higher median number of citations. As discussed above, this result is explained at least partially by Google Scholar's ranking strategies to identify articles with higher number of citations . Kalkarni et al .…”

Section: Discussionmentioning

confidence: 95%

Medical literature searches: a comparison of PubMed and Google Scholar

Nourbakhsh

Nugent

Wang

et al. 2012

Health Info Libraries J

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“…In recent years, SEO has also been applied to academic search engines, such as Google Scholar and Microsoft Academic. This new application has received the name of "academic SEO" (or ASEO) [22][23][24][25][26]. ASEO helps authors and publishers to improve the visibility of their publications, thus increasing the chances that their work will be read and cited.…”

Section: Introductionmentioning

confidence: 99%

“…Do citations received have a similarly strong influence on all these systems? A similar approach to the one adopted here has been taken in previous studies of the factors involved in the ranking of scholarly literature [22,23,[31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus

et al. 2019

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Search engine optimization (SEO) constitutes the set of methods designed to increase the visibility of, and the number of visits to, a web page by means of its ranking on the search engine results pages. Recently, SEO has also been applied to academic databases and search engines, in a trend that is in constant growth. This new approach, known as academic SEO (ASEO), has generated a field of study with considerable future growth potential due to the impact of open science. The study reported here forms part of this new field of analysis. The ranking of results is a key aspect in any information system since it determines the way in which these results are presented to the user. The aim of this study is to analyze and compare the relevance ranking algorithms employed by various academic platforms to identify the importance of citations received in their algorithms. Specifically, we analyze two search engines and two bibliographic databases: Google Scholar and Microsoft Academic, on the one hand, and Web of Science and Scopus, on the other. A reverse engineering methodology is employed based on the statistical analysis of Spearman’s correlation coefficients. The results indicate that the ranking algorithms used by Google Scholar and Microsoft are the two that are most heavily influenced by citations received. Indeed, citation counts are clearly the main SEO factor in these academic search engines. An unexpected finding is that, at certain points in time, Web of Science (WoS) used citations received as a key ranking factor, despite the fact that WoS support documents claim this factor does not intervene.

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“…In recent studies we researched the ranking algorithm of Google Scholar [1][2][3] and gave advice to researchers on how to optimize their scholarly literature for Google Scholar [4]. However, there are provisos in the academic community against what we called "Academic Search Engine Optimization" [4].…”

Section: Introductionmentioning

confidence: 99%

On the robustness of google scholar against spam

Beel

Gipp

2010

Proceedings of the 21st ACM Conference on Hypertext and Hypermedia

Self Cite

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In this research-in-progress paper we present the current results of several experiments in which we analyzed whether spamming Google Scholar is possible. Our results show, it is possible: We 'improved' the ranking of articles by manipulating their citation counts and we made articles appear in searchers for keywords the articles did not originally contained by placing invisible text in modified versions of the article.

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Google Scholar's Ranking Algorithm: The Impact of Articles' Age (An Empirical Study)

Cited by 33 publications

References 9 publications

Medical literature searches: a comparison of PubMed and Google Scholar

Medical literature searches: a comparison of PubMed and Google Scholar

Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus

On the robustness of google scholar against spam

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