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About the Digital Scholar Workbench

Text mining, or the process of deriving new information from pattern and trend analysis of the written word, has the potential to revolutionize research across subjects. Sadly, there is a massive hurdle facing those eager to unleash its power. The coding skills and statistical knowledge that text mining requires can

JSTOR Participating Publishers

JSTOR and its publishers have long been committed to text mining, with the JSTOR Data for Research (DfR) program rolling out in 2008. Our current work is an extensive expansion and improvement over the existing JSTOR text mining service. As with DfR, the new text mining platform will include content

Portico Participating Publishers

Portico publishers must choose to participate in the text analytics service. As of August 18, 2020, 42 Portico publishers have chosen to participate: Academy of Science of South AfricaBegell HouseBerghahnBioOneBond UniversityThe British Editorial Society of Bone & Joint SurgeryCambridge University PressCopernicus PublicationsCSIRO PublishingEdinburgh University PressEDP SciencesEdward Elgar PublishingEmerald Group PublishingF1000

Data Sources

JSTOR License: Non-Consumptive (Unigrams, Bigrams, Trigrams) Size: ~13.8 million documents Historical Range: 1665-present, primarily 20-21st century Metadata Quality: High Text Accuracy: High Website: https://www.jstor.org JSTOR academic sources, primarily academic journal articles in the humanities, mathematics, sciences, and business. Browse by discipline Browse by publisher Portico License:

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