In this workshop, we plan to introduce participants to a set of web-based tools for selecting and interacting with content on JSTOR via Data for Research (dfr.jstor.org), a free, self-service tool created to support data mining. Currently, Data for Research enable exploration of both scholarly journal literature (more than 7 million journal articles) and a set of primary resources (26,000 19th Century British Pamphlets). The Data for Research service is available for use by the broad research community, including independent scholars and those not affiliated with participating institutions.
We’d like to tailor the workshop to the interests of participants. Some of the possible highlights include:
- a powerful faceted search interface that can be leveraged to define content of interest through an iterative process of searching and results filtering
- word frequencies, citations, key terms, and ngrams utilized for conducting analysis of document-level data
- topic modeling (classification of subject headings at the article level), a powerful tool for content selection and filtering
- downloadable datasets containing word frequencies, citations, key terms, or ngrams associated with the content selected
- visualization tools
- API for content selection and retrieval
Are any of these areas of particular interest to you? Please comment below.