The visibility of scientific articles and conference papers is conditional upon being easily found in academic search engines, especially Google Scholar. To enhance this visibility, search engine optimization (SEO) has been …
February 10,2021 The visibility of scientific articles and conference papers is conditional upon being easily found in academic search engines, especially 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). Recent research, published in Future Internet, has found out whether the language of the document is a factor involved in the sorting algorithm of search results on Google Scholar. The study authors are Cristòfol Rovira, Lluís Codina and Carlos Lopezosa, members of the Department of Communication at UPF. “To implement this optimization we 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,” says Rovira, first author of the study. To prevent fraudulent practices, Google Scholar does not explain this algorithm and, therefore, this kind of research becomes necessary. For the study, the authors applied an inverse engineering research methodology based on statistical analysis using Spearman’s correlation coefficient.
