The interest in the (quantitative) analysis of textual data has increased considerably over the last few years. For researchers investigating the scholarly literature the full text archive of JSTOR (http://www.jstor.org) offers a rich and diverse set of journal articles and other texts. Through its service Data for Research (http://www.jstor.org/dfr/), JSTOR gives researchers the opportunity to analyse this data, by delivering metadata, n-grams and, upon special request, full-text materials. jstor (https://ropensci.github.io/jstor/) enables researchers to easily import the supplied metadata to R. These metadata can either be analysed on their own, or be used in conjunction with n-grams or full-text-data. The presentation will show how jstor supports investigations of scholarly literature, covering the analysis of n-grams and citation analysis. Besides introducing possible applications, the paper will also discuss limitations regarding data quality and possible solutions thereof.