{"product_id":"text-mining-with-r-a-tidy-approach-9781491981658","title":"Text Mining with R: A Tidy Approach","description":"\u003cp\u003eMuch of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like \u003ci\u003eggraph\u003c\/i\u003e and \u003ci\u003edplyr\u003c\/i\u003e. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.\u003c\/p\u003e\u003cp\u003eThe authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eLearn how to apply the tidy text format to NLP\u003c\/li\u003e\n\u003cli\u003eUse sentiment analysis to mine the emotional content of text\u003c\/li\u003e\n\u003cli\u003eIdentify a document's most important terms with frequency measurements\u003c\/li\u003e\n\u003cli\u003eExplore relationships and connections between words with the \u003ci\u003eggraph\u003c\/i\u003e and \u003ci\u003ewidyr\u003c\/i\u003e packages\u003c\/li\u003e\n\u003cli\u003eConvert back and forth between R's tidy and non-tidy text formats\u003c\/li\u003e\n\u003cli\u003eUse topic modeling to classify document collections into natural groups\u003c\/li\u003e\n\u003cli\u003eExamine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-11044729\"\u003eJulia Silge\u003c\/a\u003e, \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-4340262\"\u003eDavid Robinson\u003c\/a\u003e\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e O'Reilly Media\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/18\/2017\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 194\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.60lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.10h x 6.90w x 0.40d\u003cbr\u003e\u003cb\u003eISBN13:\u003c\/b\u003e 9781491981658\u003cbr\u003e\u003cb\u003eISBN10:\u003c\/b\u003e 1491981652\u003cbr\u003e\u003cb\u003eBISAC Categories:\u003c\/b\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM042000\"\u003eArtificial Intelligence | Natural Language Processing\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM089000\"\u003eData Science | Data Visualization\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM021030\"\u003eData Science | Data Analytics\u003c\/a\u003e\u003cbr\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eJulia Silge is a data scientist at Stack Overflow; her work involves analyzing complex datasets and communicating about technical topics with diverse audiences. She has a PhD in astrophysics and loves Jane Austen and making beautiful charts. Julia worked in academia and ed tech before moving into data science and discovering the statistical programming language R.\u003c\/p\u003e\u003cp\u003eDavid Robinson is a data scientist at Stack Overflow with a PhD in Quantitative and Computational Biology from Princeton University. He enjoys developing open source R packages, including broom, gganimate, fuzzyjoin and widyr, as well as blogging about statistics, R, and text mining on his blog, Variance Explained.\u003c\/p\u003e","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":45876727316655,"sku":"9781491981658","price":39.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0651\/9255\/8767\/files\/img_dcc291c9-ea13-4f93-b3ee-294e54cbfcbe.jpg?v=1757694591","url":"https:\/\/www.correctionsbookstore.com\/es\/products\/text-mining-with-r-a-tidy-approach-9781491981658","provider":"Corrections Bookstore ","version":"1.0","type":"link"}