Advances In Written Text Analysis

This work provides an overview of approaches to written text analysis, including both classic and commissioned papers which share a common linguistic framework. The examples used range from pure science, social science and periodicals to literary narratives.

This work provides an overview of a wide range of approaches to written text analysis. It includes both classic and specially commissioned papers by distinguished authors, which share a common linguistic framework. The pieces contain a variety of focuses from the patterning of paragraphs, sections or whole texts to the organization of clauses, individual expressions and single words, as well as a variety of text-types. The examples used range from pure science through social science, academic journals, weekly magazines and newspapers, to literary narratives. This collection forms the basis for an course on written text analysis that should be of interest to advanced undergraduate and postgraduate students.

Focusing on methodologies, applications and challenges of textual data analysis and related fields, this book gathers selected and peer-reviewed contributions presented at the 14th International Conference on Statistical Analysis of Textual Data (JADT 2018), held in Rome, Italy, on June 12-15, 2018. Statistical analysis of textual data is a multidisciplinary field of research that has been mainly fostered by statistics, linguistics, mathematics and computer science. The respective sections of the book focus on techniques, methods and models for text analytics, dictionaries and specific languages, multilingual text analysis, and the applications of text analytics. The interdisciplinary contributions cover topics including text mining, text analytics, network text analysis, information extraction, sentiment analysis, web mining, social media analysis, corpus and quantitative linguistics, statistical and computational methods, and textual data in sociology, psychology, politics, law and marketing.

The focus of this volume is on medical discourse, a domain of language which deserves closer scrutiny by academics as well as practitioners, due to its increasing relevance and pervasiveness in modern society. Despite the wealth of publications dealing with specialized or academic discourse and its rhetoric, few of these are devoted specifically to medical discourse. This book seeks to redress the balance by bringing together a number of studies that bear witness to the widespread interest in medical texts shown by linguists and professional communities around the world. The volume is divided into two main parts: the first targets medical discourse in its spoken dimension, while the second contains various analyses of written texts. The theoretical perspectives and individual case studies presented here reflect the wide range of methodological approaches and theoretical issues that characterise current research in the field.

Focusing on methodologies, applications and challenges of textual data analysis and related fields, this book gathers selected and peer-reviewed contributions presented at the 14th International Conference on Statistical Analysis of Textual Data (JADT 2018), held in Rome, Italy, on June 12-15, 2018. Statistical analysis of textual data is a multidisciplinary field of research that has been mainly fostered by statistics, linguistics, mathematics and computer science. The respective sections of the book focus on techniques, methods and models for text analytics, dictionaries and specific languages, multilingual text analysis, and the applications of text analytics. The interdisciplinary contributions cover topics including text mining, text analytics, network text analysis, information extraction, sentiment analysis, web mining, social media analysis, corpus and quantitative linguistics, statistical and computational methods, and textual data in sociology, psychology, politics, law and marketing.

This book is among the first to combine a historical view of media texts with a critical look at their textual diversity today. The thirteen chapters cover corpora of early news-papers and pamphlets, present-day news stories and commentaries, TV talk shows and commercials as well as internet presentations. The studies focus on the wide range of text types in 18th century newspapers and the interpersonal strategies of pamphlets; they pursue the development of the persuasive potential of headlines and advertisements right down to the sophisticated postmodernist and multilingual examples of today. Other topics are the definition and structure of news stories and commentaries, the interpersonal and multi-modal aspects of talkshows, and more radically, the questioning of the journalist's role in the age of the internet. Generally the stress is on the attention-getting side of media texts rather than on the manipulative qualities investigated by critical discourse analysis.

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.

'The editor and authors in this volume make a convincing case for focusing on advanced foreign language instruction. Importantly, they invite consideration of this focus as an opportunity to re-examine conventional definitions of the target of instruction. In so doing, readers also learn more about the theories highlighted in this volume, and their capacity to enhance our understanding of advancedness and its development within an educational context. This book thus mediates between linguistic and language learning theories and educational practice, modelling the very best of what applied linguistics has to offer.' Diane Larsen-Freeman, Professor of Education, University of Michigan. The reality of multicultural societies and globalization has increased the demand for language abilities that far exceed those that have typically been associated with communicative competence in a second language. This book examines the acquisition of advanced levels of ability in three parts: theoretical; descriptive; and instructional. It moves beyond the traditional constraints of second language acquisition research by linking systemic functional linguistics and sociocultural theory. The contributors draw primarily on the work of Halliday, Vygotsky and Bakhtin, as well as empirical data from the language classroom, to suggest practical applications towards advanced literacy and linguistic competence. Advanced Language Learning will be of interest to academics researching systemic functional linguistics, second language acquisition and applied linguistics.