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Students in social science courses communicate, socialize, shop, learn, and work online. When they are asked to collect data for course projects they are often drawn to social media platforms and other online sources of textual data. There are many software packages and programming languages available to help students collect data online, and there are many texts designed to help with different forms of online research, from surveys to ethnographic interviews. But there is no textbook available that teaches students how to construct a viable research project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives. Gabe Ignatow and Rada F. Mihalcea's new text An Introduction to Text Mining will be a starting point for undergraduates and first-year graduate students interested in collecting and analyzing textual data from online sources, and will cover the most critical issues that students must take into consideration at all stages of their research projects, including: ethical and philosophical issues; issues related to research design; web scraping and crawling; strategic data selection; data sampling; use of specific text analysis methods; and report writing.
This is the first book to treat two areas of speech synthesis: natural language processing and the inherent problems it presents for speech synthesis; and digital signal processing, with an emphasis on the concatenative approach. The text guides the reader through the material in a step-by-step easy-to-follow way. The book will be of interest to researchers and students in phonetics and speech communication, in both academia and industry.
This book provides a systematic review of many advanced techniques to support the analysis of large collections of documents, ranging from the elementary to the profound, covering all the aspects of the visualization of text documents. Particularly, we start by introducing the fundamental concept of information visualization and visual analysis, followed by a brief survey of the field of text visualization and commonly used data models for converting document into a structured form for visualization. Then we introduce the key visualization techniques including visualizing document similarity, content, sentiments, as well as text corpus exploration system in details with concrete examples in the rest of the book.
There has never been a more comprehensive resource available to teachers that does what the continuum does - provide specific behaviors and understandings that are required at each level for students to demonstrate thinking within, beyond, and about the text. These behaviors and understandings describe what students will be expected to do in order to effectively read and understand the text. More in-depth, more intuitive, and more essential than ever-The Fountas & Pinnell Literacy Continuum, Expanded Edition enables teachers to construct a common vision for student achievement that effectively and efficiently engages all students in the robust, authentic and meaningful literacy learning every child deserves. The Literacy Continuum provides a way to look for specific evidence of learning from prekindergarten through grade eight, and across eight instructional contexts. Each instructional context contributes substantially, in different but complementary ways, to students' development of the literacy process. With this indispensable literacy tool, Fountas and Pinnell remind you of The Literacy Continuum's critical role in transforming literacy teaching and learning. (Re)Discover The Fountas & Pinnell Literacy Continuum, Expanded Edition to: elevate your language and literacy expertise develop an understanding of the demands of texts on readers build your understanding of the reading and writing process and how it changes over time hone your observation of students' literacy behaviors teach toward student integration of the Systems of Strategic Actions articulate the literacy curriculum within and across grade levels activate the responsive teaching that meets students where they are and brings them forward with intention and precision build professional learning opportunities with colleagues create a common vision and common language for literacy in your school. Look for these new enhancements inside: Streamlined organization and navigation Expanded behaviors and examples across the continua First appearance of a behavior or goal or text characteristic is indicated by a red square (Behaviors are acquired and then elaborated over time) Clear organization of and explicit links to the Systems of Strategic Actions Four-color design for clarity and focus Also check out our on-demand mini-course: Thinking and Talking About Books Across the Day.
This is the ideal introduction for students seeking to collect and analyze textual data from online sources. It covers the most critical issues that they must take into consideration at all stages of their research projects.
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.
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
The New Testament, as a foundational document for millions of Christians around the world, has been the subject of intense study and scrutiny throughout history. Its text has been passed down through generations, copied by scribes, translated into numerous languages, and analyzed by scholars seeking to understand the original meaning and message of its authors. This book, "Introduction to the Text of the New Testament: From the Authors and the Scribes to the Modern Critical Texts," aims to provide readers with a comprehensive overview of the rich and complex journey that the New Testament text has taken from its inception to the present day. This work is not meant to be a mere repetition of existing scholarship; instead, it strives to synthesize the wealth of knowledge that has been accumulated on this subject and present it in a clear, accessible, and engaging manner. The chapters are organized in a logical progression, guiding readers through the various stages of the New Testament's development, including the materials used by ancient scribes, the transmission of the text, the emergence of textual families, and the various methodologies employed by scholars in their quest to recover the original text. In writing this book, we have endeavored to strike a balance between depth and accessibility, ensuring that both newcomers to the field and experienced scholars will find value in its pages. We have also made a conscious effort to be inclusive of different perspectives and methodologies, highlighting the ongoing debates and discussions within the field of New Testament textual criticism. As you embark on this journey through the history and development of the New Testament text, we hope that you will not only gain a deeper appreciation for the intricate process of textual transmission but also be inspired by the dedication and passion of the many scholars who have devoted their lives to preserving and understanding this sacred text. Ultimately, our aim is for this book to serve as a valuable resource and guide, illuminating the fascinating story behind the text that continues to shape the lives and beliefs of millions of people around the world.
The Old Testament is a treasure trove of history, culture, and spiritual wisdom. Its texts have shaped the beliefs and practices of countless individuals and communities throughout the centuries. In this book, we will embark on a journey through the text of the Old Testament, exploring its origins and development from the perspectives of the authors and scribes who created it to the modern critical text that we have today. As we delve deeper into the meaning and significance of these ancient texts, we will gain a deeper understanding of the rich cultural and religious heritage that they represent. Whether you are a student of theology, a historian, or a pastor or churchgoer who is interested in learning more about this important aspect of human history, this book will provide you with a wealth of knowledge and inspiration. So, let us begin this journey together and discover the true depth and beauty of the Old Testament.
Linguistic annotation and text analytics are active areas of research and development, with academic conferences and industry events such as the Linguistic Annotation Workshops and the annual Text Analytics Summits. This book provides a basic introduction to both fields, and aims to show that good linguistic annotations are the essential foundation for good text analytics. After briefly reviewing the basics of XML, with practical exercises illustrating in-line and stand-off annotations, a chapter is devoted to explaining the different levels of linguistic annotations. The reader is encouraged to create example annotations using the WordFreak linguistic annotation tool. The next chapter shows how annotations can be created automatically using statistical NLP tools, and compares two sets of tools, the OpenNLP and Stanford NLP tools. The second half of the book describes different annotation formats and gives practical examples of how to interchange annotations between different formats using XSLT transformations. The two main text analytics architectures, GATE and UIMA, are then described and compared, with practical exercises showing how to configure and customize them. The final chapter is an introduction to text analytics, describing the main applications and functions including named entity recognition, coreference resolution and information extraction, with practical examples using both open source and commercial tools. Copies of the example files, scripts, and stylesheets used in the book are available from the companion website, located at the book website. Table of Contents: Working with XML / Linguistic Annotation / Using Statistical NLP Tools / Annotation Interchange / Annotation Architectures / Text Analytics