Text Analysis with R for Students of Literature 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Text Analysis with R for Students of Literature

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Matthew Jockers 作者
Springer
譯者
2014-6-11 出版日期
194 頁數
USD 49.99 價格
Hardcover
叢書系列
9783319031637 圖書編碼

Text Analysis with R for Students of Literature 在線電子書 圖書標籤: R  語言學  統計學  社會學/人類學  方法論  文本  文學批評  文化   


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發表於2024-11-27

Text Analysis with R for Students of Literature 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Text Analysis with R for Students of Literature 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Text Analysis with R for Students of Literature 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



Text Analysis with R for Students of Literature 在線電子書 用戶評價

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非常好的一本書,不像有些書一樣在一些無用的基礎上長篇大論,廢話少直接上手,適閤learn by doing的人

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非常好的一本書,不像有些書一樣在一些無用的基礎上長篇大論,廢話少直接上手,適閤learn by doing的人

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文科生走嚮碼農係列之書 照著做瞭 很好玩

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還挺容易上手的

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非常好的一本書,不像有些書一樣在一些無用的基礎上長篇大論,廢話少直接上手,適閤learn by doing的人

Text Analysis with R for Students of Literature 在線電子書 著者簡介


Text Analysis with R for Students of Literature 在線電子書 著者簡介


Text Analysis with R for Students of Literature 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Text Analysis with R for Students of Literature 在線電子書 圖書描述

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.

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