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Statistics - Computational Statistics | Text Analysis with R for Students of Literature

Text Analysis with R for Students of Literature

Jockers, Matthew

2014, XVI, 194 p. 40 illus., 10 illus. in color.

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  • Book is specifically designed for students and scholars with no programming experience who wish to learn R for text analysis
  • Reader will move with ease from simple single text analysis to corpora level analysis with the accessible nature of this text, which is written from the perspective of a literature scholar
  • Design of material will get readers analyzing text immediately and covers enough conceptual information to be applied to individual projects

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. 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. 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. Each chapter builds on the previous as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying.

Content Level » Upper undergraduate

Keywords » Computational Literary Studies - Corpus Linguistics and R - Digital Humanities - Linguistic Computing - Programming and Literature - R - Text Analysis - Text Classification - Text Clustering - Text Mining

Related subjects » Computational Statistics - Linguistics - Social Sciences & Law

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