Word Frequency Distributions

This book is a comprehensive introduction to the statistical analysis of word frequency distributions, intended for computational linguists, corpus linguists, psycholinguists, and researchers in the field of quantitative stylistics.

Word Frequency Distributions

This book is a comprehensive introduction to the statistical analysis of word frequency distributions, intended for computational linguists, corpus linguists, psycholinguists, and researchers in the field of quantitative stylistics. It aims to make these techniques more accessible for non-specialists, both theoretically, by means of a careful introduction to the underlying probabilistic and statistical concepts, and practically, by providing a program library implementing the main models for word frequency distributions.

Word Frequency Studies

The series Quantitative Linguistics publishes books on all aspects of quantitative methods and models in linguistics, text analysis and related research fields.

Word Frequency Studies

The present book finds and collects absolutely new aspects of word frequency. First, eminent characteristics (such as the h-point, first used in scientometrics, the k-, m-, and n-points) are introduced - it can be shown that the geometry of word frequency is fundamentally based on them. Furthermore, various indicators of text properties are proposed for the first time, such as thematic concentration, autosemantic text compactness, autosemantic density, etc. In detail, the autosemantic structure of a given text is evaluated by means of a graph representation and its properties (according to a p.

Zipf s Law in Aphasic Speech An Investigation of Word Frequency Distributions

These insights are then used to study Zipf?s law in different types of aphasic speech: in long samples from Dutch non-fluent aphasic speakers and in short samples from English, Greek and Hungarian fluent and non-fluent aphasic speakers.

Zipf s Law in Aphasic Speech  An Investigation of Word Frequency Distributions

Word frequencies in a text follow a curious pattern. A few of them appear extremely frequently, while by far most of them appear only once or twice. This pattern is considered a law of word frequencies, and better known as Zipf?s law. The existence of this law has been known for more than a century. And yet it is still largely covered in a veil of mystery.00This dissertation aims to somewhat lift that veil. It presents a thorough discussion of the hypotheses for the existence of Zipf?s law. It is shown how the values of the parameters of Zipf?s law vary depending on medium (written or spoken) and text length. These insights are then used to study Zipf?s law in different types of aphasic speech: in long samples from Dutch non-fluent aphasic speakers and in short samples from English, Greek and Hungarian fluent and non-fluent aphasic speakers. It is shown that aphasia influences the values of the parameters, as does the language under consideration. But in all cases, Zipf?s law continues to apply. This finding strengthens the hypothesis that the system for word retrieval in aphasia is still intact.

Natural Language Processing with Python

We introduced frequency distributions in Section 1.3. We saw that given some list mylist of words or other items, FreqDist(mylist) would compute the number of occurrences of each item in the list. Here we will generalize this idea.

Natural Language Processing with Python

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.

Contemporary Advancements in Information Technology Development in Dynamic Environments

Distributions, parameters and computed determination coefficients for the frequency data of Distribution Parameters Determination coefficient a) Frequency distribution of the length of the distinct words (1) p = 0.875 R2 = 0.99179 b) ...

Contemporary Advancements in Information Technology Development in Dynamic Environments

The advancement of information technology is becoming more prevalent in all aspects of the world today, including online environments. Understanding technology’s effect on niche markets and all fields of research is crucial for practitioners in this area. Contemporary Advancements in Information Technology Development in Dynamic Environments presents an in-depth discussion into the information technology revolution present in fields such as government, gaming, social networking, and cloud computing. This book’s investigation into the research and application of information technology in several specific areas make this a useful resource for practitioners, professionals, undergraduate/graduate students, and academics.

Frequency in Language

Word frequency distributions have been studied for over a hundred years, but the results of this area of investigation are generally less well known in linguistics. Section 1.4 introduces the main players and summarizes key findings.

Frequency in Language

Re-examines frequency, entrenchment and salience, three foundational concepts in usage-based linguistics, through the prism of learning, memory, and attention.

Algorithms for Data Science

the stopwords and keeping only those words that have been used at least once by each author. The last step of the reduction produces word frequency distributions for each paper and for each author. The reader will program an algorithm ...

Algorithms for Data Science

This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses. This book has three parts:(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, the mathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials. This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.

Word Frequency Studies

all frequencies are concentrated in one word, then H = − 1 ∑ i=1 1ld1= 0 . ... The computation of entropies for the rank frequency distribution is presented in Table 9.25, for the spectra in Table 9.26 (pp. 177ff.).

Word Frequency Studies

The present book finds and collects absolutely new aspects of word frequency. First, eminent characteristics (such as the h-point, first used in scientometrics, the k-, m-, and n-points) are introduced – it can be shown that the geometry of word frequency is fundamentally based on them. Furthermore, various indicators of text properties are proposed for the first time, such as thematic concentration, autosemantic text compactness, autosemantic density, etc. In detail, the autosemantic structure of a given text is evaluated by means of a graph representation and its properties (according to a problem from network research). Special emphasis is given to the part-of-speech differentiation, which plays a significant role in stylistics. On the basis of a general theory, which has been developed especially for linguistic research, problems of the frequency structure of texts with respect to word occurrence are investigated and discussed in detail. Methodologically, specific reference is made to synergetic linguistics, including some exemplary analyses, showing that there are points of contact with this field. A separate chapter is dedicated to within-sentence word position; this issue considers grammar as well as language genesis; another chapter is dedicated to the type-token ratio, discussing all established methods and their relevance for word frequency analysis. All methods presented in the book are statistically tested; to this end, some new tests have been developed. All procedures and calculations are conducted for 20 languages, ranging from Polynesia, Indonesia, India, and Europe to a North American Indian language. The broad distribution of the data and texts from all genres allows generalizations with respect to language typology.

The Inverse Gaussian Distribution

10.6 A WORD FREQUENCY DISTRIBUTION Several statistical studies in linguistics have used word frequency and sentence length for variables . Often , empirical distributions for these variables are used to develop suitable statistical ...

The Inverse Gaussian Distribution

This monograph is a compilation of research on the inverse Gaussian distribution. It emphasizes the presentation of the statistical properties, methods, and applications of the two-parameter inverse Gaussian family of distribution. It is useful to statisticians and users of statistical distribution.

Quantitative Linguistik Quantitative Linguistics

In: Literary and Linguistic Computing 13 (2), 77K 87. 30. Word frequency distributions Introduction The urn model LNRE models Traditional approaches to word frequency distributions Literature (a selection) 1. 2. 3. 4.

Quantitative Linguistik   Quantitative Linguistics

Over the past two decades, statistical and other quantitative concepts, models and methods have been increasingly gaining importance and interest in all areas of linguistics and text analysis, as well as in a number of neighboring disciplines and areas of application. The term "quantitative linguistics" comprises all scientific and technical approaches which use such terms and methods in the analysis of or work with language(s), texts and other related subjects. The 71 articles in this handbook, written by internationally-recognized experts, offer a broad, up-to-date overview of the scientific-theoretical principles, the history, the diversity of the subject areas studied, the methods and models used, the results obtained thus far and their applications. The articles are divided up into thirteen chapters: the first chapter includes contributions on the basic principles and the history of the field, nine additional chapters are dedicated to individual descriptions of the levels of linguistic research (from phonology to pragmatics) as well as typological, diachronic and geolinguistic questions. The next two chapters include a description of important models, hypotheses and principles; selected areas of application; and references to neighboring disciplines. The last portion of the handbook is an informative contribution, with information about publication forums, bibliographies, major projects, Internet links, etc. This handbook is useful not only for researchers, teachers and students of all branches of linguistics and the philologies, but also for scientists in neighboring fields, whose theoretical and empirical research touches on linguistic questions (for instance, psychology and sociology), or for those who want to make use of the proven methods or results from quantitative linguistics in their own research.

Morphological Structure in Language Processing

given a particular value of X, E[Y | X]? In the case of a bivariate standard normal distribution with slope not greater than 1, ... The corresponding expression for word frequency distributions can be found in Good (1953).

Morphological Structure in Language Processing

This volume brings together a series of studies of morphological processing in Germanic (English, German, Dutch), Romance (French, Italian), and Slavic (Polish, Serbian) languages. The question of how morphologically complex words are organized and processed in the mental lexicon is addressed from different theoretical perspectives (single and dual route models), for different modalities (auditory and visual comprehension, writing), and for language development. Experimental work is reported, as well as computational and statistical modeling. Thus, this volume provides a useful overview of the range of issues currently attracting reseach at the intersection of morphology and psycholinguistics.

Corpus Linguistics and Statistics with R

8.8 Probability Distributions So far in this book we have worked with frequency distributions. The outcome of a counting experiment is always specific to the sample that it was computed from. If we replicate a word count on other ...

Corpus Linguistics and Statistics with R

This textbook examines empirical linguistics from a theoretical linguist’s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.

A Concordance to the Works of Christopher Marlowe

As expected , the number of different words equals the total number of words in a very short passage . ... Frequency distributions for word and sentence length and other characteristics that were given numerically for each text ...

A Concordance to the Works of Christopher Marlowe


Morphology Morphology its relation to semantics and the lexicon

These processes show up with the frequency distributions with the greatest degree of skewing in favor of lowfrequency ... are characterized by large numbers of hard - worked , high - frequency words and only small numbers of hapaxes .

Morphology  Morphology  its relation to semantics and the lexicon

This six-volume collection draws together the most significant contributions to morphological theory and analysis which all serious students of morphology should be aware of. By comparing the stances taken by the different schools about the important issues, the reader will be able to judge the merits of each, with the benefit of evidence rather than prejudice.