"Networks of Language" will interest all those concerned with the acquisition and everyday operations of language, in particular scholars and advanced students in linguistics, psychology, and cognitive

A comprehensive account of the neurobiological basis of language, arguing that species-specific brain differences may be at the root of the human capacity for language. Language makes us human. It is an intrinsic part of us, although we seldom think about it. Language is also an extremely complex entity with subcomponents responsible for its phonological, syntactic, and semantic aspects. In this landmark work, Angela Friederici offers a comprehensive account of these subcomponents and how they are integrated. Tracing the neurobiological basis of language across brain regions in humans and other primate species, she argues that species-specific brain differences may be at the root of the human capacity for language. Friederici shows which brain regions support the different language processes and, more important, how these brain regions are connected structurally and functionally to make language processes that take place in milliseconds possible. She finds that one particular brain structure (a white matter dorsal tract), connecting syntax-relevant brain regions, is present only in the mature human brain and only weakly present in other primate brains. Is this the “missing link” that explains humans' capacity for language? Friederici describes the basic language functions and their brain basis; the language networks connecting different language-related brain regions; the brain basis of language acquisition during early childhood and when learning a second language, proposing a neurocognitive model of the ontogeny of language; and the evolution of language and underlying neural constraints. She finds that it is the information exchange between the relevant brain regions, supported by the white matter tract, that is the crucial factor in both language development and evolution.

This monograph takes up recent advances in social network methods in sociology, together with data on economic segregation, in order to build a quantitative analysis of the class and network effects implicated in vowel change in a Southern American city. Studies of sociolinguistic variation in urban spaces have uncovered durable patterns of linguistic difference, such as the maintenance of blue collar/white collar distinctions in the case of stable linguistic variables. But the underlying interactional origins of these patterns, and the interactional reasons for their durability, are not well understood, due in part to the near-absence of large-scale network investigation. This book undertakes a sociolinguistic network analysis of data from the Raleigh corpus, a set of conversational interviews collected form natives of Raleigh, North Carolina, from 2008-2017. Acoustic analysis of the corpus shows the rapid, ongoing retreat from the Southern Vowel Shift and increasing participation in national vowel changes. The social distribution of these trends is explored via standard social factors such as occupation as well as innovative network variables, including a measure of nestedness in the community network. The book aims to pursue new network-based questions about sociolinguistic variation that can be applied to other corpora, making this key reading for students and researchers in sociolinguistics and historical linguistics as well as those interested in further understanding how existing quantitative network methods from sociological research might be applied to sociolinguistic data.

The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities. This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statistical models of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information science. It may also be of interest for the upcoming area of systems biology with which the chapters collected here share the view on systems from the point of view of network analysis.

This pioneering research brings a new insight into derivational processes in terms of theory, method and typology. Theoretically, it conceives of derivation as a three-dimensional system. Methodologically, it introduces a range of parameters for the evaluation of derivational networks, including the derivational role, combinability and blocking effects of semantic categories, the maximum derivational potential and its actualization in relation to simple underived words, and the maximum and average number of orders of derivation. Each language-specific chapter has a unified structure, which made it possible to identify – in the final, typologically oriented chapter – the systematicity and regularity in developing derivational networks in a sample of forty European languages and in a few language genera and families. This is supported by considerations about the role of word-classes, morphological types, and the differences and similarities between word-formation processes of the languages belonging to the same genus/family.

The Linguistic Cerebellum provides a comprehensive analysis of this unique part of the brain that has the most number of neurons, each operating in distinct networks to perform diverse functions. This book outlines how those distinct networks operate in relation to non-motor language skills. Coverage includes cerebellar anatomy and function in relation to speech perception, speech planning, verbal fluency, grammar processing, and reading and writing, along with a discussion of language disorders. - Discusses the neurobiology of cerebellar language functions, encompassing both normal language function and language disorders - Includes speech perception, processing, and planning - Contains cerebellar function in reading and writing - Explores how language networks give insight to function elsewhere in the brain

Provides a dynamic network model of grammar that explains how linguistic structure is shaped by language use.

Based on an investigation into the urban vernacular of Belfast.

Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.

Metaphor Networks focuses on the historical evolution of metaphor and proposes new theories on language change based on substantial empirical data. It explores how the metaphors of today are very often linked to images existing in the past and traces metaphor paths back to the Middle Ages and Antiquity. The findings reveal that regular patters of evolution emerge and the aims of the book are to find out what lies behind these patterns.