A Guide to English: Text Analysis / Distant Reading

"How does a literary historian end up thinking in terms of z-scores, principal component analysis, and clustering coefficients? The 10 essays in Distant Reading led to a new and often contested paradigm of literary analysis. In presenting them here Franco Moretti reconstructs his intellectual trajectory, the theoretical influences over his work, and explores the polemics that have often developed around his positions. From the evolutionary model of 'Modern European Literature', through the geo-cultural insights of 'Conjectures on World Literature' and 'Planet Hollywood' to the quantitative findings of 'Style, inc.' and the abstract patterns of 'Network Theory, Plot Analysis', the book follows two decades of critical explorations that have come to define--well beyond the wildest expectations of its author--a growing field of unorthodox literary studies." - from the publisher

"Just as a traveler crossing a continent won't sense the curvature of the earth, one lifetime of reading can't grasp the largest patterns organizing literary history. This is the guiding premise behind Distant Horizons, which uses the scope of data newly available to us through digital libraries to tackle previously elusive questions about literature. Ted Underwood shows how digital archives and statistical tools, rather than reducing words to numbers (as is often feared), can deepen our understanding of issues that have always been central to humanistic inquiry. Without denying the usefulness of time-honored approaches like close reading, narratology, or genre studies, Underwood argues that we also need to read the larger arcs of literary change that have remained hidden from us by their sheer scale. Using both close and distant reading to trace the differentiation of genres, transformation of gender roles, and surprising persistence of aesthetic judgment, Underwood shows how digital methods can bring into focus the larger landscape of literary history and add to the beauty and complexity we value in literature." - from the publisher

"A theoretical and practical guide to using corpus linguistic techniques in stylistic analysis. The use of corpora in stylistics has increased substantially in recent years but until now there has been no book detailing the theoretical basis and methodological practices of corpus stylistics. This book surveys the field and sets the agenda for this fast-developing area. Focusing on how to use off-the-shelf corpus software, such as AntConc, Wmatrix, and the Brigham Young University (BYU) corpus interface, this step-by-step guide explains the theory and practice of using corpus methods and tools for stylistic analysis. Eight original case studies demonstrate how to use corpus tools to analyse style in a range of texts, from the contemporary to the historical. McIntyre and Walker explain how to develop appropriate research questions for corpus stylistic analysis, construct and annotate corpora, make sense of statistics, and analyse corpus data. In addition, the book provides practical advice on how to manage the transition from quantitative results to qualitative analysis, and explores how theories, models and frameworks from stylistics can be used to enhance the qualitative phase of corpus analysis. Supported by detailed instructions on how to access and use relevant corpus software, this is a user’s guide to doing corpus stylistic analysis. For students and researchers in stylistics new to the use of corpus methods and theories, the book presents a ‘how-to’ guide; for corpus linguists it opens the door to the theories, models and frameworks developed in stylistics that are of value to mainstream corpus linguistics."

"Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context"-- Provided by publisher.

This fourth edition "provides a comprehensive guide to conducting content analysis research. It establishes a formal definition of quantitative content analysis; gives step-by-step instructions on designing a content analysis study; and explores in depth several recurring questions that arise in such areas as measurement, sampling, reliability, data analysis, and the use of digital technology in the content analysis process. It maintains the concise, accessible approach of the first three editions while offering updated discussions and examples. It examines in greater detail the use of computers to analyze content and how that process varies from human coding of content, incorporating more literature about technology and content analysis throughout. Updated topics include sampling in the digital age, computerized content analysis as practiced today, and incorporating social media in content analysis. Each chapter contains useful objectives and chapter summaries to cement core concepts." -- Back cover.

"This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find both fascinating and immensely useful." - from the publisher

"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." - from the publisher

"This is the first book of its kind to provide a practical and student-friendly guide to corpus linguistics that explains the nature of electronic data and how it can be collected and analyzed. Designed to equip readers with the technical skills necessary to analyze and interpret language data, both written and (orthographically) transcribed. Introduces a number of easy-to-use, yet powerful, free analysis resources consisting of standalone programs and web interfaces for use with Windows, Mac OS X, and Linux. Each section includes practical exercises, a list of sources and further reading, and illustrated step-by-step introductions to analysis tools. Requires only a basic knowledge of computer concepts in order to develop the specific linguistic analysis skills required for understanding/analyzing corpus data." - from the publisher