This collection was compiled by an international group of scholars in recognition of Professor Yiwola Awoyale’s contributions to African language and linguistic studies. Based at University of Pennsylvania, Professor Awoyale is particularly celebrated as a great field linguist, who pays special attention to data and data documentation. This edited volume presents current research on topics concerning the syntax, semantics, phonology, applied- and socio-linguistics of African languages, providing a state-of-the-art account of contemporary issues in African linguistics today.

Cognitive linguistics has an honourable tradition of paying respect to naturally occurring language data and there have been fruitful interactions between corpus data and aspects of linguistic structure and meaning. More recently, dialect data and sociolinguistic data collection methods/theoretical concepts have started to generate interest. There has also been an increase in several kinds of experimental work. However, not all linguistic data is simply naturally occurring or derived from experiments with statistically robust samples of speakers. Other traditions, especially the generative tradition, have fruitfully used introspection and questions about the grammaticality of different strings to uncover patterns which might otherwise have gone unnoticed. The divide between generative and cognitive approaches to language is intimately connected to the kinds of data drawn on, and the way in which generalisations are derived from these data. The papers in this volume explore these issues through the lens of synchronic linguistic analysis, the study of language change, typological investigation and experimental study. Originally published in Studies in Language Vol. 36:3 (2012).

From Data to Evidence in English Language Research draws on diverse digital data sources alongside more traditional linguistic corpora to offer new insights into the ways in which they can be used to extend and re-evaluate research questions in English linguistics. This is achieved, for example, by increasing data size, adding multi-layered contextual analyses, applying methods from adjacent fields, and adapting existing data sets to new uses. Making innovative contributions to digital linguistics, the chapters in the volume apply a combination of methods to the increasing amount of digital data available to researchers to show how this data – both established and newly available - can be utilized, enriched and rethought to provide new evidence for developments in the English language.

In Corpus Linguistics and Sociolinguistics, Beke Hansen analyses variation and change in the modal systems of three second-language varieties of English in Asia by taking a sociolinguistic approach to corpus data. Her study focuses on the modal and semi-modal verbs of strong obligation and necessity in Hong Kong English, Indian English, and Singapore English based on the relevant ICE component corpora. She adopts a typologically-informed perspective on variation in World Englishes by comparing the structures of the speakers’ first languages with the structures of the emergent varieties in the expression of epistemic modality. Beyond this, she analyses language change by constructing apparent-time scenarios to compensate for the lack of diachronic corpora in World Englishes.

In recent decades, corpus linguistics has experienced tremendous development in the Hispanic world, along two opposite but complementary approaches: increase in corpus size (corpus linguistics as Big Data) and improvement in document selection and data annotation (corpus linguistics as High Quality Data). The first approach has led to the creation of massive corpora such as EsTenTen; at the same time, it has promoted the use of the web and social networks as corpora. The second perspective gives rise to specialized corpora such as Post Scriptum or Oralia Diacrónica del español (ODE). The contributions gathered in this volume combine both methods in order to exploit their advantages and to overcome their possible limitations. On the one hand, it addresses the creation and design of small corpora focused on data quality; on the other hand, it offers case studies that make use of both specialized corpora and massive data extracted from the web. Highlighting the complementary nature of both methods is the main idea of this book.

This book is an essential read for any professional dealing with data and information challenges. Imagine a collection of villages all beset upon by monsters. One village defeats their monsters using silver bullets. They convince all surrounding villages that their solution should be the only standard. The next village uses silver bullets to repel the monsters but fail! Why? Because the first village was fighting werewolves, the second village was fighting vampires. This is our data challenge–recognizing not all problems are the same - and there are no single silver bullet solutions. There are many communities within financial services, each with nuanced needs that require slightly different solutions to address what may look like the same problem. The financial services industry is unique for being based upon information and communication. It is the failure in understanding that multiple existing financial languages exist and pursuing interoperability that sits at the crux of financial crisis – not the lack of a single unified financial language. This book is an essential read for any professional dealing with data and information challenges. The author presents a new, unique approach to broad industry issues, leveraging applied linguistics and discusses how to break barriers that exist between language and data; the aim to make it easier for the financial industry (including regulators) to communicate - for the benefit of all investors. Unconventional in the cross-disciplinary pairing of applied linguistics and financial services, it is practical and intuitive in pursuing solutions. While focused on financial services, the approach is relevant for other industries that have similar challenges.

Biblical and Ancient Greek Linguistics (BAGL) is an international journal that exists to further the application of modern linguistics to the study of Ancient and Biblical Greek, with a particular focus on the analysis of texts, including but not restricted to the Greek New Testament. The journal is hosted by McMaster Divinity College and works in conjunction with its Centre for Biblical Linguistics, Translation and Exegesis, and the OpenText.org organization (www.opentext.org) in the sponsoring of conferences and symposia open to scholars and students working in Greek linguistics who are interested in contributing to advancing the discussion and methods of the field of research. BAGL is a refereed on-line and print journal dedicated to distributing the results of significant research in the area of linguistic theory and application to biblical and ancient Greek, and is open to all scholars, not just those connected to the Centre and the OpenText.org project.

This two-volume set, consisting of LNCS 7816 and LNCS 7817, constitutes the thoroughly refereed proceedings of the 13th International Conference on Computer Linguistics and Intelligent Processing, CICLING 2013, held on Samos, Greece, in March 2013. The total of 91 contributions presented was carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections named: general techniques; lexical resources; morphology and tokenization; syntax and named entity recognition; word sense disambiguation and coreference resolution; semantics and discourse; sentiment, polarity, subjectivity, and opinion; machine translation and multilingualism; text mining, information extraction, and information retrieval; text summarization; stylometry and text simplification; and applications.

Contemporary data analytics involves extracting insights from data and translating them into action. With its turn towards empirical methods and convergent data sources, cognitive linguistics is a fertile context for data analytics. There are key differences between data analytics and statistical analysis as typically conceived. Though the former requires the latter, it emphasizes the role of domain-specific knowledge. Statistical analysis also tends to be associated with preconceived hypotheses and controlled data. Data analytics, on the other hand, can help explore unstructured datasets and inspire emergent questions. This volume addresses two key aspects in data analytics for cognitive linguistic work. Firstly, it elaborates the bottom-up guiding role of data analytics in the research trajectory, and how it helps to formulate and refine questions. Secondly, it shows how data analytics can suggest concrete courses of research-based action, which is crucial for cognitive linguistics to be truly applied. The papers in this volume impart various data analytic methods and report empirical studies across different areas of research and application. They aim to benefit new and experienced researchers alike.

This easy-to-follow book will revolutionise how you approach text mining and data analysis as well as equipping you with the tools, and confidence, to navigate complex qualitative data. It can be challenging to effectively combine theoretical concepts with practical, real-world applications but this accessible guide provides you with a clear step-by-step approach. Written specifically for students and early career researchers this pragmatic manual will: • Contextualise your learning with real-world data and engaging case studies. • Encourage the application of your new skills with reflective questions. • Enhance your ability to be critical, and reflective, when dealing with imperfect data. Supported by practical online resources, this book is the perfect companion for those looking to gain confidence and independence whilst using transferable data skills.