When you hear the words "in the original text it says" or "in the original text this means," it's time to be wary. Those words often provide the introduction to misleading information. But how can the hearer discern just what is correct and what is misleading? How can pastors avoid giving their congregations misleading information? "In the Original Text It Says" takes a look at word-study fallacies and how you can avoid them. Author Ben Baxter gives an introduction to word meaning and how word meaning differs between languages. He then examines a series of fallacies, errors that people make in assigning meaning to words in the original languages of the Bible. But he doesn't leave it with that theoretical examination. After providing the basis for how to understand Biblical words, he examines the discussion of specific words and phrases from passages in both the Old Testament and the New. He takes these examples from commentaries commonly used by pastors and teachers in sermon and lesson preparation. With each example, he shows how one might misunderstand the linguistic evidence provided, and also how one can properly apply this information. This book is designed for readers who have had some contact with Greek or Hebrew, but will also be useful to those who have more language skill, but may not have studied linguistics or looked carefully at how to apply their knowledge in teaching.

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.

Take our word for it - you'll love expressing yourself with Text It quilts! Share a sentiment, stitch an inspiring statement, or create cute and quirky messages in fabric. Use the letters, numbers, and symbols of seven different fonts, provided on pullout pattern sheets, to create 10 quilt and pillow patterns as shown in the book. Or personalize projects with one-of-a-kind wordplay! Applique text with a variety of techniques, including fusible, bias-strip, and needle-turn applique, plus English paper piecing. Mix and match lettering styles (choose from print and cursive), sizes, colors, and fabrics for layers of creative fun. From clever catchphrases to sayings that are good for the soul, choose just the right words to convey your thoughts in fabric.

Summary Taming Text, winner of the 2013 Jolt Awards for Productivity, is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built. About this Book There is so much text in our lives, we are practically drowningin it. Fortunately, there are innovative tools and techniquesfor managing unstructured information that can throw thesmart developer a much-needed lifeline. You'll find them in thisbook. Taming Text is a practical, example-driven guide to working withtext in real applications. This book introduces you to useful techniques like full-text search, proper name recognition,clustering, tagging, information extraction, and summarization.You'll explore real use cases as you systematically absorb thefoundations upon which they are built.Written in a clear and concise style, this book avoids jargon, explainingthe subject in terms you can understand without a backgroundin statistics or natural language processing. Examples arein Java, but the concepts can be applied in any language. Written for Java developers, the book requires no prior knowledge of GWT. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. Winner of 2013 Jolt Awards: The Best Books—one of five notable books every serious programmer should read. What's Inside When to use text-taming techniques Important open-source libraries like Solr and Mahout How to build text-processing applications About the Authors Grant Ingersoll is an engineer, speaker, and trainer, a Lucenecommitter, and a cofounder of the Mahout machine-learning project. Thomas Morton is the primary developer of OpenNLP and Maximum Entropy. Drew Farris is a technology consultant, software developer, and contributor to Mahout,Lucene, and Solr. "Takes the mystery out of verycomplex processes."—From the Foreword by Liz Liddy, Dean, iSchool, Syracuse University Table of Contents Getting started taming text Foundations of taming text Searching Fuzzy string matching Identifying people, places, and things Clustering text Classification, categorization, and tagging Building an example question answering system Untamed text: exploring the next frontier

The first coherent theoretical, critical, and editorial approach to the study of literary revision

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A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry

"As . . . newer approaches [to biblical criticism] become more established and influential, it is essential that students and other serious readers of the Bible be exposed to them and become familiar with them. That is the main impetus behind the present volume, which is offered as a textbook for those who wish to go further than the approaches covered in To Each Its Own Meaning by exploring more recent or experimental ways of reading." „from the introduction This book is a supplement and sequel to To Each Its Own Meaning, edited by Steven L. McKenzie and Stephen R. Haynes, which introduced the reader to the most important methods of biblical criticism and remains a widely used classroom textbook. This new volume explores recent developments in, and approaches to, biblical criticism since 1999. Leading contributors define and describe their approach for non-specialist readers, using examples from the Old and New Testament to help illustrate their discussion. Topics include cultural criticism, disability studies, queer criticism, postmodernism, ecological criticism, new historicism, popular culture, postcolonial criticism, and psychological criticism. Each section includes a list of key terms and definitions and suggestions for further reading.