Language Bias in the Google Scholar Ranking Algorithm

Cristòfol Rovira, Lluís Codina and Carlos Lopezosa
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Cristòfol Rovira: Department of Communication, Universitat Pompeu Fabra, 08002 Barcelona, Spain
Lluís Codina: Department of Communication, Universitat Pompeu Fabra, 08002 Barcelona, Spain
Carlos Lopezosa: Department of Communication, Universitat Pompeu Fabra, 08002 Barcelona, Spain

Future Internet, 2021, vol. 13, issue 2, 1-17

Abstract: The visibility of academic articles or conference papers depends on their being easily found in academic search engines, above all in Google Scholar. To enhance this visibility, search engine optimization (SEO) has been applied in recent years to academic search engines in order to optimize documents and, thereby, ensure they are better ranked in search pages (i.e., academic search engine optimization or ASEO). To achieve this degree of optimization, we first need to further our understanding of Google Scholar’s relevance ranking algorithm, so that, based on this knowledge, we can highlight or improve those characteristics that academic documents already present and which are taken into account by the algorithm. This study seeks to advance our knowledge in this line of research by determining whether the language in which a document is published is a positioning factor in the Google Scholar relevance ranking algorithm. Here, we employ a reverse engineering research methodology based on a statistical analysis that uses Spearman’s correlation coefficient. The results obtained point to a bias in multilingual searches conducted in Google Scholar with documents published in languages other than in English being systematically relegated to positions that make them virtually invisible. This finding has important repercussions, both for conducting searches and for optimizing positioning in Google Scholar, being especially critical for articles on subjects that are expressed in the same way in English and other languages, the case, for example, of trademarks, chemical compounds, industrial products, acronyms, drugs, diseases, etc.

Keywords: ASEO; SEO; reverse engineering; citations; google scholar; algorithms; relevance ranking; citation databases; academic search engines; multilingual search (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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