Web application in Shiny for the extraction of data from profiles in Google Scholar

Abstract

The need to measure the contribution of researchers through academic profiles is of great importance, which is why in 2018 we created an algorithm in R language to dynamically extract data from individual and institutional public p rofiles in Google Scholar Citations. Although the algorithm has been of great use in the automatic extraction of data, allowing statistical reports and analyzes to be carried out with this data, it is only possible to use it if the user knows the R language, due to the multiple functions that the R language has integrated. algorithm. In this work we show the creation of a web application integrating the algorithm to extract data from Google Scholar Citation s but improving the ease of use of these scripts using the R Shiny package, which integrates web components from Rstudio but maintaining the programming characteristics of the language. . Shiny converts scripts into interactive web applications, without any knowledge of HTML, CSS or Javascript, making it e asy for users to use, manipulate, view, and allow for future updates to improve functionality. The results of the tests and tasks carried out in this work show that the use of the web application in Shiny, the extraction algorithm could be integrated without difficulty, improving the extraction time in seconds and minutes, because the user does not interact with it. R code but with the Web interface allowing users new to R who are dedicated to the analysis of Google Scholar data to use it.

A Web Scraper for Data Mining Purposes

“…Their designed scraper was efficient in retrieving data successfully. In fact, there are many recent articles about scraping Google Scholar such as [15], [16], [17], [18], [19], [20]. Table 1 presents a summary of the studies considered in this section in terms of the main observed limitations.…”