Programming For Corpus Linguistics With Python And Dataframes PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Programming For Corpus Linguistics With Python And Dataframes PDF full book. Access full book title Programming For Corpus Linguistics With Python And Dataframes.

Programming for Corpus Linguistics with Python and Dataframes

Programming for Corpus Linguistics with Python and Dataframes
Author: Daniel Keller
Publisher: Cambridge University Press
Total Pages: 226
Release: 2024-06-30
Genre: Language Arts & Disciplines
ISBN: 1108916384
GET BOOK

Download Programming for Corpus Linguistics with Python and Dataframes Book in PDF, ePub and Kindle

This Element offers intermediate or experienced programmers algorithms for Corpus Linguistic (CL) programming in the Python language using dataframes that provide a fast, efficient, intuitive set of methods for working with large, complex datasets such as corpora. This Element demonstrates principles of dataframe programming applied to CL analyses, as well as complete algorithms for creating concordances; producing lists of collocates, keywords, and lexical bundles; and performing key feature analysis. An additional algorithm for creating dataframe corpora is presented including methods for tokenizing, part-of-speech tagging, and lemmatizing using spaCy. This Element provides a set of core skills that can be applied to a range of CL research questions, as well as to original analyses not possible with existing corpus software.

Essential Python for Corpus Linguistics

Essential Python for Corpus Linguistics
Author: Mark Johnson
Publisher: Wiley-Blackwell
Total Pages: 208
Release: 2008
Genre: Computers
ISBN: 9781405145640
GET BOOK

Download Essential Python for Corpus Linguistics Book in PDF, ePub and Kindle

Linguistic research increasingly relies on large electronic corpora for its primary data. While off-the-shelf programs can perform a set of standard searches, specialized questions usually require a custom-written program to find their answers. Essential Python for Corpus Linguistics uses the programming language Python to explain how to write simple programs that extract linguistically useful information, such as the frequency of a given utterance in a particular context within a corpus, or instances of certain phrasal structures in a Treebank. Assuming no prior programming background, the book provides numerous example programs that search for phonological, morphological and syntactic constructions in corpora, and the associated web site provides sample data and programs, which make it easy to start working independently. This book is a valuable resource for linguists who use corpus methods but have no programming training.

Python Programming for Linguistics and Digital Humanities

Python Programming for Linguistics and Digital Humanities
Author: Martin Weisser
Publisher: John Wiley & Sons
Total Pages: 295
Release: 2024-01-31
Genre: Computers
ISBN: 1119907942
GET BOOK

Download Python Programming for Linguistics and Digital Humanities Book in PDF, ePub and Kindle

Learn how to use Python for linguistics and digital humanities research, perfect for students working with Python for the first time Python programming is no longer only for computer science students; it is now an essential skill in linguistics, the digital humanities (DH), and social science programs that involve text analytics. Python Programming for Linguistics and Digital Humanities provides a comprehensive introduction to this widely used programming language, offering guidance on using Python to perform various processing and analysis techniques on text. Assuming no prior knowledge of programming, this student-friendly guide covers essential topics and concepts such as installing Python, using the command line, working with strings, writing modular code, designing a simple graphical user interface (GUI), annotating language data in XML and TEI, creating basic visualizations, and more. This invaluable text explains the basic tools students will need to perform their own research projects and tackle various data analysis problems. Throughout the book, hands-on exercises provide students with the opportunity to apply concepts to particular questions or projects in processing textual data and solving language-related issues. Each chapter concludes with a detailed discussion of the code applied, possible alternatives, and potential pitfalls or error messages. Teaches students how to use Python to tackle the types of problems they will encounter in linguistics and the digital humanities Features numerous practical examples of language analysis, gradually moving from simple concepts and programs to more complex projects Describes how to build a variety of data visualizations, such as frequency plots and word clouds Focuses on the text processing applications of Python, including creating word and frequency lists, recognizing linguistic patterns, and processing words for morphological analysis Includes access to a companion website with all Python programs produced in the chapter exercises and additional Python programming resources Python Programming for Linguistics and Digital Humanities: Applications for Text-Focused Fields is a must-have resource for students pursuing text-based research in the humanities, the social sciences, and all subfields of linguistics, particularly computational linguistics and corpus linguistics.

Quantitative Corpus Linguistics with R

Quantitative Corpus Linguistics with R
Author: Stefan Th. Gries
Publisher: Taylor & Francis
Total Pages: 287
Release: 2016-10-14
Genre: Education
ISBN: 1317597664
GET BOOK

Download Quantitative Corpus Linguistics with R Book in PDF, ePub and Kindle

As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on: data processing and manipulation in general; text processing with and without regular expressions of large bodies of textual and/or literary data, and; basic aspects of statistical analysis and visualization. This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.

Natural Language Processing for Corpus Linguistics

Natural Language Processing for Corpus Linguistics
Author: Jonathan Dunn
Publisher: Cambridge University Press
Total Pages: 149
Release: 2022-03-31
Genre: Language Arts & Disciplines
ISBN: 1009083740
GET BOOK

Download Natural Language Processing for Corpus Linguistics Book in PDF, ePub and Kindle

Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora. These computational methods are becoming increasingly important as corpora grow too large for more traditional types of linguistic analysis. We draw on five case studies to show how and why to use computational methods, ranging from usage-based grammar to authorship analysis to using social media for corpus-based sociolinguistics. Each section is accompanied by an interactive code notebook that shows how to implement the analysis in Python. A stand-alone Python package is also available to help readers use these methods with their own data. Because large-scale analysis introduces new ethical problems, this Element pairs each new methodology with a discussion of potential ethical implications.

Natural Language Processing with Python

Natural Language Processing with Python
Author: Steven Bird
Publisher: "O'Reilly Media, Inc."
Total Pages: 506
Release: 2009-06-12
Genre: Computers
ISBN: 0596555717
GET BOOK

Download Natural Language Processing with Python Book in PDF, ePub and Kindle

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.

Exploring Linguistic Science

Exploring Linguistic Science
Author: Allison Burkette
Publisher:
Total Pages: 253
Release: 2018-03-15
Genre: Language Arts & Disciplines
ISBN: 1108424805
GET BOOK

Download Exploring Linguistic Science Book in PDF, ePub and Kindle

Introduces students to the scientific study of language, using the basic principles of complexity theory.

Applied Text Analysis with Python

Applied Text Analysis with Python
Author: Rebecca Bilbro
Publisher:
Total Pages: 350
Release: 2018
Genre: Python (Computer program language)
ISBN: 9781491963036
GET BOOK

Download Applied Text Analysis with Python Book in PDF, ePub and Kindle

With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. You’ll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. The programming landscape of natural language processing has changed dramatically in the past few years. Machine learning approaches now require mature tools like Python’s scikit-learn to apply models to text at scale. This practical guide shows programmers and data scientists who have an intermediate-level understanding of Python and a basic understanding of machine learning and natural language processing how to become more proficient in these two exciting areas of data science. This book presents a concise, focused, and applied approach to text analysis with Python, and covers topics including text ingestion and wrangling, basic machine learning on text, classification for text analysis, entity resolution, and text visualization. Applied Text Analysis with Python will enable you to design and develop language-aware data products. You’ll learn how and why machine learning algorithms make decisions about language to analyze text; how to ingest, wrangle, and preprocess language data; and how the three primary text analysis libraries in Python work in concert. Ultimately, this book will enable you to design and develop language-aware data products.

Corpus Approaches to Language in Social Media

Corpus Approaches to Language in Social Media
Author: Matteo Di Cristofaro
Publisher:
Total Pages: 0
Release: 2024
Genre: Corpora (Linguistics)
ISBN: 9781032125725
GET BOOK

Download Corpus Approaches to Language in Social Media Book in PDF, ePub and Kindle

"This book showcases the unique possibilities of corpus linguistic methodologies in engaging with and analysing language data from social media, surveying current approaches and offering guidelines and best practices for doing language analysis. The volume provides an overview of how language in social media has been approached by both linguists and non-linguists, before digging deeper into the identification of datasets needs to fill linguistic investigations of social media and the technical aspects of particular platforms which may influence analysis, such as emoticons, retweets, and metadata. Sample Python code, along with general guidelines for using it, are provided to empower researchers to apply these techniques in their own work, supported by actual examples from three real-life case studies. Di Cristofaro highlights the full potential of using these methodologies in analysing social media language data and the ways in which they might pave the way for future applications of data analysis and processing for corpus linguistics. The book will be key reading for researchers in corpus linguistics and linguists and social scientists interested in data-driven analysis of social media"--