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Why OCR? Campus resources Computational Text Analysis Working Group D-Lab This group of graduate students, faculty and researchers meet twice a month during the semester to share research, provide technical workshops, and offer space to support ongoing analysis.

D-Lab Trainings D-Lab helps Berkeley faculty, staff, and graduate students move forward with world-class research in data intensive social science. R R is a free software environment for statistical computing and graphics.

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Lightning Review: Text Analysis with R for Students of Literature

RStudio is a development interface for R featuring a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management. Mallet MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. Digital Scholar Lab Gale.


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The Digital Scholar Lab has cloud-based tools for automatically performing common computational queries on and creating visualizations from content sets built with Gale primary source collections. Declassified Documents Online. Shop Books.


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  • Add to Wishlist. USD Overview Text Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text.

    Table of contents

    Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R.

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    R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale.

    Text Analysis with R for Students of Literature | Matthew Jockers | Springer

    About the Author The author, Matthew L. Table of Contents R Basics.

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