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    1. Text-mining Group | Duke University Libraries

      Text-mining Group | Duke University Libraries Skip to main content My Accounts Ask a Librarian Library Hours Search our Site ☰ (...)

    2. Text Mining Documentation Directions | Duke University Libraries

      Text Mining Documentation Directions | Duke University Libraries Skip to main content My Accounts Ask a Librarian Library (...)

    3. Text Mining Talk > TODAY at 2:30 - Duke University Libraries Blogs

      Text Mining Talk > TODAY at 2:30 - Duke University Libraries Blogs Go Search Announcement , Events , Humanities , Instruction (...)

    4. Topic Modeling/Text Mining - DH Boot Camp for Librarians - LibGuides at Duke University

      Topic Modeling/Text Mining - DH Boot Camp for Librarians - LibGuides at Duke University Skip to Main Content Home LibGuides DH (...)

    5. Tackling the Law of Text and Data Mining for Computational Research - Duke University Libraries Blog

      Tackling the Law of Text and Data Mining for Computational Research - Duke University Libraries Blogs Go Search Announcement , (...)

    6. Text Visualization - Introduction to Text Analysis - LibGuides at Duke University

      Text Visualization - Introduction to Text Analysis - LibGuides at Duke University Skip to Main (...)

    7. About Text Analysis - Introduction to Text Analysis - LibGuides at Duke University

      Overviews/summaries Ted Underwood – Where to start with text mining Tooling Up for Digital Humanities – Text (...)

    8. About Text Analysis - Introduction to Text Analysis - LibGuides at Duke University

      Overviews/summaries Ted Underwood – Where to start with text mining Tooling Up for Digital Humanities – Text (...)

    9. Analysis Methods and Tools - Introduction to Text Analysis - LibGuides at Duke University

      Dictionary tagging (locating a specific set of words in the texts) High-level Goals for Text Analysis (From Underwood, T. (2012). Where (...)

    10. Why TEI? Text > Data Thursday - Duke University Libraries Blogs

      Is it the anti-thesis of text-mining? What’s it’s value for researchers who need to read texts in different ways?

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