Automating Linguistics offers an in-depth study of the history of the mathematisation and automation of the sciences of language. In the wake of the first mathematisation of the 1930s, two waves followed: machine translation in the 1950s and the development of computational linguistics and natural language processing in the 1960s. These waves were pivotal given the work of large computerised corpora in the 1990s and the unprecedented technological development of computers and software.Early machine translation was devised as a war technology originating in the sciences of war, amidst the amalgamate of mathematics, physics, logics, neurosciences, acoustics, and emerging sciences such as cybernetics and information theory. Machine translation was intended to provide mass translations for strategic purposes during the Cold War. Linguistics, in turn, did not belong to the sciences of war, and played a minor role in the pioneering projects of machine translation.Comparing the two trends, the present book reveals how the sciences of language gradually integrated the technologies of computing and software, resulting in the second-wave mathematisation of the study of language, which may be called mathematisation-automation. The integration took on various shapes contingent upon cultural and linguistic traditions (USA, ex-USSR, Great Britain and France). By contrast, working with large corpora in the 1990s, though enabled by unprecedented development of computing and software, was primarily a continuation of traditional approaches in the sciences of language sciences, such as the study of spoken and written texts, lexicography, and statistical studies of vocabulary.

Presenting a detailed examination of the origins, evolutions, and state-of-the-art of linguistic landscape research, The Bloomsbury Handbook of Linguistic Landscapes is a comprehensive guide to the burgeoning field of linguistic landscapes and the study of meaning and interpretation in public spaces and settings. Providing a thorough synopsis of the theories, methodologies, and objects of study which inflect linguistic landscape research across the world, this book is the ideal companion for both new and experienced readers interested in the processes of communication in public spaces across diverse settings and from a broad range of perspectives. Through a wide selection of case studies and original research, the handbook highlights the global reach of linguistic landscape theories and practices. Scrutinising an array of qualitative, quantitative, and mixed methodological approaches for analysing a wide spectrum of meaning-making phenomena, it investigates semiosis in contexts ranging from graffiti and street signs to tattoos and literature, visible across a variety of sites, including city centres, rural settings, schools, protest marches, museums, war-torn landscapes, and the internet.

Statutory warning: Language is a minefield. Words that firms and consumers use can be dealbreakers! Today, firms have many language-based decisions to make—from the brand name to the language of their annual reports to what they should or shouldn’t say on social media. Moreover, consumers leave a goldmine of information via their words expressing their likes, dislikes, perceptions and attitudes. What the firm communicates and what consumers say have an impact on consumer attitudes, satisfaction, loyalty, and ultimately, on a firm's sales, market share and profits. In this book, Abhishek Borah meticulously and marvellously showcases the influence of language on business. Through examples ranging from Toyota to Tesla and Metallica to Mahatma Gandhi, you will read about how to improvise on social media, how changing the use of simple pronouns like ‘we’ and ‘you’ can affect a firm’s bottom line, how to spot a fake review online and much more. So whether you are just inquisitive about the role of language in affecting consumer and company behaviour or a student wondering about the utility of language analysis in understanding them, Mine Your Language will teach you to use language to influence, engage and predict!

Linguistics: The Study of Language is an insightful exploration into the world of language and its intricate structure. This book offers a comprehensive guide through the various branches of linguistics, providing readers with an in-depth understanding of how language is formed, used, and evolves over time. From the basics of phonetics and phonology to the complexities of syntax and semantics, this book covers every aspect of language study. It delves into the cognitive processes behind language acquisition, the social factors influencing language use, and the neural mechanisms that enable language processing in the brain. Each chapter is meticulously structured to guide the reader through the foundational concepts and advanced topics, making it an essential resource for both beginners and seasoned linguists. The book also touches on the practical applications of linguistics in the real world, including language teaching, translation, computational linguistics, and forensic analysis. By examining the role of language in society and the impact of technology on communication, this book equips readers with the knowledge to understand the ever-evolving nature of human language. Whether you’re a student of linguistics, a language enthusiast, or someone interested in understanding the nuances of human communication, Linguistics: The Study of Language provides a clear and engaging overview of one of humanity’s most fundamental tools.

A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.

Solving linguistic problems not infrequently is reduced to carrying out tasks that are computationally complex and therefore requires automation. In such situations, the difference between having and not having computational tools to handle the tasks is not a matter of economy of time and effort, but may amount to the difference between finding and not finding a solution at all. This book is an introduction to machine-aided linguistic discovery, a novel research area, arguing for the fruitfulness of the computational approach by presenting a basic conceptual apparatus and several intelligent discovery programmes. One of the systems models the fundamental Saussurian notion of system, and thus, for the first time, almost a century after the introduction of this concept and structuralism in general, linguists are capable of adequately handling this recurring, computationally complex task. Another system models the problem of searching for Greenbergian language universals and is capable of stating its discoveries in an intelligible form, viz. a comprehensive English language text, thus constituting the first computer program to generate a whole scientific article. Yet another system detects potential inconsistencies in genetic language classifications. The programmes are applied with noteworthy results to substantial problems from diverse linguistic disciplines such as structural semantics, phonology, typology and historical linguistics.

This book presents new and innovative current discoveries in social networking which contribute enough knowledge to the research community. The book includes chapters presenting research advances in social network analysis and issues emerged with diverse social media data. The book also presents applications of the theoretical algorithms and network models to analyze real-world large-scale social networks and the data emanating from them as well as characterize the topology and behavior of these networks. Furthermore, the book covers extremely debated topics, surveys, future trends, issues, and challenges.

The attempt to spot deception through its correlates in human behavior has a long history. Until recently, these efforts have concentrated on identifying individual "cues" that might occur with deception. However, with the advent of computational means to analyze language and other human behavior, we now have the ability to determine whether there are consistent clusters of differences in behavior that might be associated with a false statement as opposed to a true one. While its focus is on verbal behavior, this book describes a range of behaviors—physiological, gestural as well as verbal—that have been proposed as indicators of deception. An overview of the primary psychological and cognitive theories that have been offered as explanations of deceptive behaviors gives context for the description of specific behaviors. The book also addresses the differences between data collected in a laboratory and "real-world" data with respect to the emotional and cognitive state of the liar. It discusses sources of real-world data and problematic issues in its collection and identifies the primary areas in which applied studies based on real-world data are critical, including police, security, border crossing, customs, and asylum interviews; congressional hearings; financial reporting; legal depositions; human resource evaluation; predatory communications that include Internet scams, identity theft, and fraud; and false product reviews. Having established the background, this book concentrates on computational analyses of deceptive verbal behavior that have enabled the field of deception studies to move from individual cues to overall differences in behavior. The computational work is organized around the features used for classification from -gram through syntax to predicate-argument and rhetorical structure. The book concludes with a set of open questions that the computational work has generated.