A New Webliography of Text Mining Resources
The Science and Technology Resources on the Internet column in the Spring 2017 issue of Issues in Science and Technology Librarianship includes a webliography of text mining resources.
This useful resource was compiled and written by Kristen Cooper, a librarian at the award-winning University of Minnesota Libraries in Minneapolis.
From the Webliography:
This webliography is intended as an overview for those in higher education, such as academic librarians, researchers, educators, and graduate students, who are interested in text mining but have little to no experience with it.
Resources for the webliography were compiled from the author’s previous research, communications with fellow librarians experienced in text mining, and text mining library guides from the Universities of Southern California (2016), California San Diego (2016), Illinois at Urbana-Champaign (2016), Duke (2016), and Chicago (2016) were consulted. In order to be included resources had to meet the following criteria:
- Available in English,
- Available via library subscription or freely available,
- Information is published, maintained, and/or hosted by reputable source, and
- Explanations and examples are clear and appropriate for beginner
Resources are organized into the following sections:
- Scope and Methods
- Introductory Resources
- Sources of Text
- Library Databases
- Online Sources
Direct to Full Text: “Text Mining” by Kristen Cooper
About Gary Price
Gary Price (email@example.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.