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Text Analysis With R For Students Of Literature
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Book Synopsis Text Analysis with R by : Matthew L. Jockers
Download or read book Text Analysis with R written by Matthew L. Jockers and published by Springer Nature. This book was released on 2020-03-30 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each 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. Text Analysis with R 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 toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.
Download or read book Text Mining with R written by Julia Silge and published by "O'Reilly Media, Inc.". This book was released on 2017-06-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.
Book Synopsis Supervised Machine Learning for Text Analysis in R by : Emil Hvitfeldt
Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.
Book Synopsis Text Analysis with R by : Matthew Lee Jockers
Download or read book Text Analysis with R written by Matthew Lee Jockers and published by . This book was released on 2020 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction explores core R procedures and processes and offers a thorough understanding of the possibilities of computational text analysis at both micro and macro scales. Each chapter concludes with a set of practice exercises.
Book Synopsis Text Analysis with R for Students of Literature by : Matthew Jockers
Download or read book Text Analysis with R for Students of Literature written by Matthew Jockers and published by Springer. This book was released on 2014-06-14 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Applied Text Analysis with Python by : Benjamin Bengfort
Download or read book Applied Text Analysis with Python written by Benjamin Bengfort and published by "O'Reilly Media, Inc.". This book was released on 2018-06-11 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity
Book Synopsis Text Analysis with R for Students of Literature by : Matthew L. Jockers
Download or read book Text Analysis with R for Students of Literature written by Matthew L. Jockers and published by Springer. This book was released on 2014-06-10 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Qualitative Text Analysis by : Udo Kuckartz
Download or read book Qualitative Text Analysis written by Udo Kuckartz and published by SAGE. This book was released on 2014-01-23 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can you analyse narratives, interviews, field notes, or focus group data? Qualitative text analysis is ideal for these types of data and this textbook provides a hands-on introduction to the method and its theoretical underpinnings. It offers step-by-step instructions for implementing the three principal types of qualitative text analysis: thematic, evaluative, and type-building. Special attention is paid to how to present your results and use qualitative data analysis software packages, which are highly recommended for use in combination with qualitative text analysis since they allow for fast, reliable, and more accurate analysis. The book shows in detail how to use software, from transcribing the verbal data to presenting and visualizing the results. The book is intended for Master’s and Doctoral students across the social sciences and for all researchers concerned with the systematic analysis of texts of any kind.
Book Synopsis Humanities Data in R by : Taylor Arnold
Download or read book Humanities Data in R written by Taylor Arnold and published by Springer Nature. This book was released on with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Macroanalysis by : Matthew L. Jockers
Download or read book Macroanalysis written by Matthew L. Jockers and published by University of Illinois Press. This book was released on 2013-04-15 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this volume, Matthew L. Jockers introduces readers to large-scale literary computing and the revolutionary potential of macroanalysis--a new approach to the study of the literary record designed for probing the digital-textual world as it exists today, in digital form and in large quantities. Using computational analysis to retrieve key words, phrases, and linguistic patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the "close-reading" of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections.
Book Synopsis Textual Analysis Made Easy by : C. Brian Taylor
Download or read book Textual Analysis Made Easy written by C. Brian Taylor and published by Routledge. This book was released on 2016-10-04 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this new book, you’ll learn how to teach evidence-based writing using a variety of tools, activities, and sample literary texts. Showing elementary and middle school students how to think critically about what they’re reading can be a challenge, but author C. Brian Taylor makes it easy by presenting twelve critical thinking tools along with step-by-step instructions for implementing each one effectively in the classroom. You’ll learn how to: Design units and lesson plans that gradually introduce your students to more complex levels of textual analysis; Encourage students to dig deeper by using the 12 Tools for Critical Thinking; Help students identify context and analyze quotes with the Evidence Finder graphic organizer; Use the Secret Recipe strategy to construct persuasive evidence-based responses that analyze a text’s content or technique; Create Cue Cards to teach students how to recognize and define common literary devices. The book also offers a series of extra examples using mentor texts, so you can clearly see how the strategies in this book can be applied to excerpts from popular, canonical, and semi-historical literature. Additionally, a number of the tools and templates in the book are available as free eResources from our website (http://www.routledge.com/9781138950658), so you can start using them immediately in your classroom.
Book Synopsis How to Analyse Texts by : Ronald Carter
Download or read book How to Analyse Texts written by Ronald Carter and published by Routledge. This book was released on 2015-08-20 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to Analyse Texts is the essential introductory textbook and toolkit for language analysis. This book shows the reader how to undertake detailed, language-focussed, contextually sensitive analyses of a wide range of texts – spoken, written and multimodal. The book constitutes a flexible resource which can be used in different ways across a range of courses and at different levels. This textbook includes: three parts covering research and study skills, language structure and use, and how texts operate in sociocultural contexts a wide range of international real-life texts, including items from South China Morning Post, art’otel Berlin and Metro Sweden, which cover digital and print media, advertising, recipes and much more objectives and skill review for each section, activities, commentaries, suggestions for independent assignments, and an analysis checklist for students to follow a combined glossary and index and a comprehensive further reading section a companion website at www.routledge.com/cw/goddard with further links and exercises for students. Written by two experienced teachers of English Language, How to Analyse Texts is key reading for all students of English language and linguistics.
Book Synopsis Text Analysis for the Social Sciences by : Carl W. Roberts
Download or read book Text Analysis for the Social Sciences written by Carl W. Roberts and published by Routledge. This book was released on 1997 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides descriptions and illustrations of cutting-edge text analysis methods for communication and market research, cultural, historical-comparative, and event analysis, curriculum evaluation, psychological diagnosis, language development research, and for any research in which statistical inferences are drawn from samples of texts. Although the book is accessible to readers having no experience with content analysis, the text analysis expert will find substantial new material in its pages. The methods presented here will be useful for international research, as well as for practitioners from the fields of sociology, political science, journalism/communication, computer science, marketing, education, and English.
Book Synopsis Close Reading: The Basics by : David Greenham
Download or read book Close Reading: The Basics written by David Greenham and published by Routledge. This book was released on 2018-07-27 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Close reading is the most essential skill that literature students continue to develop across the full length of their studies. This book is the ideal guide to the practice, providing a methodology that can be used for poetry, novels, drama, and beyond. Using classic works of literature, such as Hamlet and The Great Gatsby as case studies, David Greenham presents a unique, contextual approach to close reading, while addressing key questions such as: What is close reading? What is the importance of the relationships between words? How can close reading enhance reading pleasure? Is there a method of close reading that works for all literary genres? How can close reading unlock complexity? How does the practice of close reading relate to other theoretical and critical approaches? Close Reading: The Basics is formulated to bring together reading pleasure and analytic techniques that will engage the student of literature and enhance their reading experience.
Book Synopsis Learning Statistics with R by : Daniel Navarro
Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Book Synopsis Analysing Practical and Professional Texts by : Rod Watson
Download or read book Analysing Practical and Professional Texts written by Rod Watson and published by Routledge. This book was released on 2016-04-08 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysing Practical and Professional Texts focuses on texts as constituents of human usage, showing how written documents and other 'texts' are integral to social organization. It reveals social organization itself to be not only textually-mediated in nature, but also textually-constituted, showing how texts - professional, technical or otherwise - as well as various social-scientific methodologies employ the resources of ordinary language. Theoretically sophisticated and illustrated with empirical examples, this book will be of interest not only to those with interests in ethnomethodology and conversation analysis, but also to social scientists and anthropologists concerned with text analysis, textual sense and the 'linguistic turn' in the methods of their own disciplines.
Book Synopsis Automated Data Collection with R by : Simon Munzert
Download or read book Automated Data Collection with R written by Simon Munzert and published by John Wiley & Sons. This book was released on 2015-01-20 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands on guide to web scraping and text mining for both beginners and experienced users of R Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. Provides basic techniques to query web documents and data sets (XPath and regular expressions). An extensive set of exercises are presented to guide the reader through each technique. Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. Case studies are featured throughout along with examples for each technique presented. R code and solutions to exercises featured in the book are provided on a supporting website.
