An Exploration of Mendeley Reader and Google Scholar Citation for Analysing Indexed Article

Abstract— This paper aims to analyze the number of readers from the published articles of 100 Indonesian researchers in Mendeley reference management software. The list of Indonesian scientists is obtained from the webometrics ranking of scientists. We used the Application Programming Interface (API) of Mendeley to count the number of readers for each article in Mendeley and combine it with Google Scholar citation using the scrap method. We processed ten mostly cited articles that are indexed in the first page of the Google Scholar for each designated scientist. Furthermore, we used the Pearson method to analyze the correlation of the Mendeley readers count and the Google Scholar citation. The results show that they are correlated with a value of 0.266 according to the method of Pearson with N = 1000. Furthermore we found that many online Indonesian journals have no Digital Object Identifier (DOI) yet. Our evaluation of the publication results of 100 Indonesian researchers shows that authors who upload their scientific work on Mendeley, have higher citation number in Google Scholar, because their papers are widely available on the Internet.