Appliable Approaches to Analyzing Texts in Academic Discourse


Book Description

This book provides a comprehensive overview of approaches to problems of language learning, aimed at graduate students and researchers interested in English for academic purposes. Its primary focus is the complexity and nuances of academic writing such as phraseology, nominalization, thematicity, and phrasal complexity features. The book will clarify the issue of how language is used to communicate discipline-related content, viewed through the lens of linguistics as one of the human sciences. Each chapter concludes with several tasks that enable users to substantiate what has been presented in that chapter. The book primarily addresses non-native speakers of English who are studying for master’s and PhD qualifications through the medium of English; however, non-native researchers may also find some chapters of the book useful for their underlying focus on academic writing and publishing.







Text Analysis with R


Book Description

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.




Text as Data


Book Description

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




Analyzing Everyday Texts


Book Description

In Analyzing Everyday Texts, author Glenn F. Stillar provides a comprehensive and well-illustrated framework for the analysis of everyday texts by outlining and integrating three different perspectives: discoursal, rhetorical, and social. First, the tools of each perspective are carefully explicated in chapters on the resources of discoursal, rhetorical, and social theory. These three perspectives are then brought together in extensive analyses of various everyday texts. Finally, the book reflects on the principles and consequences of conducting theoretically informed critical textual analysis. For researchers analyzing everyday texts and for scholars teaching theories and methods of analysis, Analyzing Everyday Texts will be an invaluable addition to the current literature.




Analyzing Text and Discourse


Book Description

A unique anthology of textual analysis methodologies, this book offers a thorough introduction to the key approaches and the tools students need to implement them. Every chapter contains not just the theory behind each methodology, but also its advantages and disadvantages, its problems with ontology and language, and its relationship to studying social phenomenon. Through contemporary and relatable real-world worked examples, the book illustrates different contexts in which a methodology has been successfully used and allows students to see the methods in action and extrapolate the techniques into their own research. Methods included: Content analysis Argumentation analysis Qualitative analysis of ideas Narrative analysis Metaphor analysis Multimodal discourse analysis Discourse analysis Engaging and authoritative in equal measure, this guide to textual analysis is the perfect foundation for students conducting research in the social sciences.




Analyzing Discourse and Text Complexity for Learning and Collaborating


Book Description

With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL) and e-learning technologies, the need of automatic assessment and of teacher/tutor support for the two tightly intertwined activities of comprehension of reading materials and of collaboration among peers has grown significantly. In this context, a polyphonic model of discourse derived from Bakhtin’s work as a paradigm is used for analyzing both general texts and CSCL conversations in a unique framework focused on different facets of textual cohesion. As specificity of our analysis, the individual learning perspective is focused on the identification of reading strategies and on providing a multi-dimensional textual complexity model, whereas the collaborative learning dimension is centered on the evaluation of participants’ involvement, as well as on collaboration assessment. Our approach based on advanced Natural Language Processing techniques provides a qualitative estimation of the learning process and enhances understanding as a “mediator of learning” by providing automated feedback to both learners and teachers or tutors. The main benefits are its flexibility, extensibility and nevertheless specificity for covering multiple stages, starting from reading classroom materials, to discussing on specific topics in a collaborative manner and finishing the feedback loop by verbalizing metacognitive thoughts.




Handbook of Language Analysis in Psychology


Book Description

Recent years have seen an explosion of interest in the use of computerized text analysis methods to address basic psychological questions. This comprehensive handbook brings together leading language analysis scholars to present foundational concepts and methods for investigating human thought, feeling, and behavior using language. Contributors work toward integrating psychological science and theory with natural language processing (NLP) and machine learning. Ethical issues in working with natural language data sets are discussed in depth. The volume showcases NLP-driven techniques and applications in areas including interpersonal relationships, personality, morality, deception, social biases, political psychology, psychopathology, and public health.




Appliable Linguistics and Social Semiotics


Book Description

Exploring the relationship between theory and practice in Systemic Functional Linguistics (SFL), this volume offers a state-of-the-art overview of Appliable Linguistics. Featuring both internationally-renowned scholars and rising stars from Argentina, Australia, Austria, Brazil, Chile, Denmark, Indonesia, New Zealand, Singapore and the USA, Appliable Linguistics and Social Semiotics examines the theoretical insights, questions, and developments that have emerged from the application of Systemic Functional theory to a range of fields. Beyond simply reporting on the application of SFL to particular sites of communication, both linguistic and semiotic, this volume demonstrates how SFL has critiqued, developed and transformed theory and practice and foregrounds the implications of application for Systemic Functional theory itself. Covering established fields for application, such as education, medicine and media, to relatively uncharted areas, such as software design and extremist propaganda, this volume provides an overview of recent linguistic and semiotic innovations informed by SFL and examines the advances that have been made from many years of productive dialogue between theory and practice.




Analysing Structure in Academic Writing


Book Description

This book breaks through formalistic traditions to propose a new generic structure analytical framework for academic writing. The integrated approach, taking lessons from cognitive linguistics and structuralism, offers a foundation for establishing research and pedagogy that can promote diversity and inclusion in academia. The simplicity of the flexible structure analytical model proposed by Sawaki enables the user to analyse diverse instances of genre. Further innovation is made in the analysis of generic structure components by integrating George Lakoff and Mark Johnson’s metaphor analysis method, so that the model can account for cultural and ideological patterns that structure our abstract thinking. Using these integrations, the author has established a structure analytical model that can take into account linguistic, cognitive, and pragmatic aspects of genre. Researchers in the fields of linguistics, discourse studies, cultural studies, education, and English for Academic Purposes will be able to use this model to identify whether an atypical instance in academic texts is a result of the writer’s individual failure or a failure to understand diversity in academic writing.