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BEGIN:VEVENT
DTSTART:20200304T170000Z
DTEND:20200304T180000Z
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SUMMARY:Digital Brown Bag | Conducting bibliometric research with tidyJSTOR
DESCRIPTION:JSTOR Data for Research allows researchers to text mine content 
 in JSTOR’s extensive archive of scholarly literature\;  journal 
 articles\, primary sources\, and books\; textual content (metadata or 
 OCR-ed full text) can be assembled into a downloadable dataset for analysis 
 with one’s own tools. Arthur Netto\, a Ph.D. student at the University of 
 São Paulo and fellow of the Center for the History of Political Economy at 
 Duke University\, started using R bibliometric tools to make NGRAM plots of 
 JSTOR data\, but found he needed – and then created – more functions 
 for analyzing the content. He wrapped everything into a single R package 
 – tidyJSTOR – and uploaded the package to Github in order to 
 disseminate it and receive comments on code and functions.\n\nAt this 
 Digital Brown Bag talk\, Arthur will talk about the research questions 
 motivating his use of JSTOR’s Data for Research\, the potential and 
 limitations of existing R bibliometric tools\, and the additional features 
 he’s built into tidyJSTOR. As a self-taught R user and self-taught user 
 of bibliometrics\, he’s also eager to hear others’ approaches and 
 suggestions. If you’d like to check out tidyJSTOR before the talk\, 
 please do! You can access the tool and the tutorial here: 
 https://github.com/arthurbnetto/tidyJSTOR.
LOCATION:Bostock 121 (Murthy Digital Studio)\, West Campus
ORGANIZER;CN="Liz Milewicz":MAILTO:liz.milewicz@duke.edu
CATEGORIES:Digital Scholarship, Scholarly Communications
CONTACT;CN="Liz Milewicz":MAILTO:liz.milewicz@duke.edu
STATUS:CONFIRMED
UID:LibCal-5734992
URL:https://duke.libcal.com/event/5734992
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