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Specialists in quantitative linguistics the world over have recourse to a solid and universal methodology. These days, their methods and mathematical models must also respond to new communication phenomena and the flood of data produced daily. While various disciplines (computer science, media science) have different ways of processing this onslaught of information, the linguistic approach is arguably the most relevant and effective. This book includes recent results from many renowned contemporary practitioners in the field. Our target audiences are academics, researchers, graduate students, and others involved in linguistics, digital humanities, and applied mathematics.
The edited volume Motifs in Language and Text is the first collection of original research in the area of the quantitative analysis of motifs. It hosts a collection of contributions that give insight to linguistic motifs theoretically across different languages, text genres, and structural levels, such as lexical, syntactic, semantic etc., and also to the tentative efforts upon the practical applications of the linguistic motifs. .
Founding Editor: Gabriel Altmann The series Quantitative Linguistics publishes books on all aspects of quantitative methods and models in linguistics, text analysis and related research fields. Specifically, the scope of the series covers the whole spectrum of theoretical and empirical research, ultimately striving for an exact mathematical formulation and empirical testing of hypotheses: observation and description of linguistic data, application of methods and models, discussion of methodological and epistemological issues, modelling of language and text phenomena.
The edited volume Sequences in Language and Text is the first collection of original research in the area of the quantitative analysis of sequentially organized linguistic data. Linguistic sequences are extremely useful textual structures in almost all areas of Language Technology. Character and word n-grams are by far the most successful features in text classification tasks such as authorship identification, text categorization, genre classification, sentiment analysis etc. Furthermore character linguistic sequences are the basis for linguistic modeling and subsequent applications such as speech recognition, language identification etc. In addition to the above language technology oriented research, the present volume aims to give insight to the theoretical value of linguistic sequences. Sequences in texts can be produced by a number of different factors, either external to the linguistic system or by its own grammatical structure. This volume hosts contributions which will analyze linguistic sequences using quantitative methods under the synergetic theoretical framework that can explain their role in the linguistic system.
This comprehensive and detailed analysis of second language writers' text identifies explicitly and quantifiably where their text differs from that of native speakers of English. The book is based on the results of a large-scale study of university-level native-speaker and non-native-speaker essays written in response to six prompts. Specifically, the research investigates the frequencies of uses of 68 linguistic (syntactic and lexical) and rhetorical features in essays written by advanced non-native speakers compared with those in the essays of native speakers enrolled in first-year composition courses. The selection of features for inclusion in this analysis is based on their textual functions and meanings, as identified in earlier research on English language grammar and lexis. Such analysis is valuable because it can inform the teaching of grammar and lexis, as well as discourse, and serve as a basis for second language curriculum and course design; and provide valuable insight for second language pedagogical applications of the study's findings.
Contributions in this book illustrate the many methods available for researching language in context and for the analysis of everyday text types. Each chapter highlights language as a resource for the expression of meanings—a social semiotic resource. Text analysis is used to reveal our capacity to formulate multiple meanings for participation in different social practices—in relationships, in work, in education and in leisure. The approach is applied in text-based teaching and in the critical analysis of public discourses. The texts come from different social spheres including banking, language classes, senate hearings, national tests and textbooks, and interior architecture. Text-based research makes a major contribution to Critical Discourse Analysis. The editors and authors of this book demonstrate the value of text analysis for awareness of the role of language for accountable citizenship and for teaching and learning. This book will be of interest to anyone researching in the fields of language learning and teaching, functional linguistics, multimodality, social semiotics, systemic functional linguistics, text-based teaching, and genre analysis, as well as literacy teachers and undergraduate and postgraduate students of linguistics, media and education.
This book explains the detectionbased approach to investigating crosslinguistic influence and illustrates the value of the approach through a collection of five empirical studies that use the approach to quantify, evaluate, and isolate the subtle and complex influences of learners’ nativelanguage backgrounds on their English writing.
In Language Online, David Barton and Carmen Lee investigate the impact of the online world on the study of language. The effects of language use in the digital world can be seen in every aspect of language study, and new ways of researching the field are needed. In this book the authors look at language online from a variety of perspectives, providing a solid theoretical grounding, an outline of key concepts, and practical guidance on doing research. Chapters cover topical issues including the relation between online language and multilingualism, identity, education and multimodality, then conclude by looking at how to carry out research into online language use. Throughout the book many examples are given, from a variety of digital platforms, and a number of different languages, including Chinese and English. Written in a clear and accessible style, this is a vital read for anyone new to studying online language and an essential textbook for undergraduates and postgraduates working in the areas of new media, literacy and multimodality within language and linguistics courses.
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. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence 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 Natural Language Processing with Python both fascinating and immensely useful.