A Manual Of Textual Analysis

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A Manual Of Textual Analysis

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Author : Vinton Adams Dearing
language : en
Publisher:
Release Date : 1959

A Manual Of Textual Analysis written by Vinton Adams Dearing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1959 with Bible categories.

A Manual Of Textual Analysis

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Author : Vinton Adams Dearing
language : en
Publisher: Greenwood Publishing Group
Release Date : 1983-01-01

A Manual Of Textual Analysis written by Vinton Adams Dearing and has been published by Greenwood Publishing Group this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983-01-01 with Religion categories.

A theory and method of textual analysis which according to the author, may be applied to the transmission and embodiment in any form of any idea or complex of ideas, but was developed specifically to deal with the complicated interrelations of the manuscripts of the Bible, especially of the Greek New Testament.

Manual Of Textual Analysis

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Author : Vinton A. Dearing
language : en
Publisher: Univ of California Press
Release Date : 2022-08-19

Manual Of Textual Analysis written by Vinton A. Dearing and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-19 with Language Arts & Disciplines categories.

This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1959.

The Content Analysis Guidebook

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Author : Kimberly A. Neuendorf
language : en
Publisher: SAGE Publications
Release Date : 2016-04-25

The Content Analysis Guidebook written by Kimberly A. Neuendorf and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-25 with Language Arts & Disciplines categories.

Content analysis is one of the most important but complex research methodologies in the social sciences. In this thoroughly updated Second Edition of The Content Analysis Guidebook, author Kimberly Neuendorf draws on examples from across numerous disciplines to clarify the complicated aspects of content analysis through step-by-step instruction and practical advice. Throughout the book, the author also describes a wide range of innovative content analysis projects from both academia and commercial research that provide readers with a deeper understanding of the research process and its many real-world applications.

Text Mining With R

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Author : Julia Silge
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-06-12

Text Mining With R written by Julia Silge and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-12 with Computers categories.

Much 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 ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The 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. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document’s most important terms with frequency measurements Explore relationships and connections between words with the ggraph and widyr packages Convert back and forth between R’s tidy and non-tidy text formats Use topic modeling to classify document collections into natural groups Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages

Food Analysis Laboratory Manual

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Author : S. Suzanne Nielsen
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-20

Food Analysis Laboratory Manual written by S. Suzanne Nielsen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-20 with Technology & Engineering categories.

This second edition laboratory manual was written to accompany Food Analysis, Fourth Edition, ISBN 978-1-4419-1477-4, by the same author. The 21 laboratory exercises in the manual cover 20 of the 32 chapters in the textbook. Many of the laboratory exercises have multiple sections to cover several methods of analysis for a particular food component of characteristic. Most of the laboratory exercises include the following: introduction, reading assignment, objective, principle of method, chemicals, reagents, precautions and waste disposal, supplies, equipment, procedure, data and calculations, questions, and references. This laboratory manual is ideal for the laboratory portion of undergraduate courses in food analysis.

Text Analysis With R

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Author : Matthew L. Jockers
language : en
Publisher: Springer Nature
Release Date : 2020-03-30

Text Analysis With R written by Matthew L. Jockers and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-30 with Computers categories.

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.

Introducing Electronic Text Analysis

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Author : Svenja Adolphs
language : en
Publisher: Routledge
Release Date : 2006-09-27

Introducing Electronic Text Analysis written by Svenja Adolphs and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-27 with Language Arts & Disciplines categories.

Introducing Electronic Text Analysis is a practical and much needed introduction to corpora – bodies of linguistic data. Written specifically for students studying this topic for the first time, the book begins with a discussion of the underlying principles of electronic text analysis. It then examines how these corpora enhance our understanding of literary and non-literary works. In the first section the author introduces the concepts of concordance and lexical frequency, concepts which are then applied to a range of areas of language study. Key areas examined are the use of on-line corpora to complement traditional stylistic analysis, and the ways in which methods such as concordance and frequency counts can reveal a particular ideology within a text. Presenting an accessible and thorough understanding of the underlying principles of electronic text analysis, the book contains abundant illustrative examples and a glossary with definitions of main concepts. It will also be supported by a companion website with links to on-line corpora so that students can apply their knowledge to further study. The accompanying website to this book can be found at http://www.routledge.com/textbooks/0415320216

Qualitative Content Analysis

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Author : Philipp Mayring
language : en
Publisher: SAGE
Release Date : 2021-11-03

Qualitative Content Analysis written by Philipp Mayring and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-03 with Reference categories.

This book is a systematic, eight-step guide to qualitative content analysis, supporting you through each stage of your research project, no matter the type or amount of data.

Text Data Management And Analysis

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Author : ChengXiang Zhai
language : en
Publisher: Morgan & Claypool
Release Date : 2016-06-30

Text Data Management And Analysis written by ChengXiang Zhai and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-30 with Computers categories.

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.