The main goal of this research note is to educate business researchers on how to automatically scrape financial data from the World Wide Web using the R programming language. This paper is organized into the following main parts. The first part provides a conceptual overview of the web scraping process. The second part educates the reader about the Rvest package—a popular tool for browsing and downloading web data in R. The third part educates the reader about the main functions of the XBRL package. The XBRL package was developed specifically for working with financial data distributed using the XBRL format in the R environment. The fourth part of this paper presents an example of a relatively complex web scraping task implemented using the R language. This complex web scraping task involves using both the Rvest and XBRL packages for the purposes of retrieving, preprocessing, and organizing financial and nonfinancial data related to a company from various sources and using different data forms. The paper ends with some concluding remarks on how the web scraping approach presented in this paper can be useful in other research projects involving financial and nonfinancial data.

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