Computational Text Analysis
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Mapping Texts
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Author : Dustin S. Stoltz
language : en
Publisher: Oxford University Press
Release Date : 2024
Mapping Texts written by Dustin S. Stoltz and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Computers categories.
Mapping Texts is the first introduction to computational text analysis that simultaneously blends conceptual treatments with practical, hands-on examples that walk the reader through how to conduct text analysis projects with real data. The book shows how to conduct text analysis in the R statistical computing environment--a popular programming language in data science.
Text Analysis With R
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Author : Matthew L. Jockers
language : en
Publisher: Springer
Release Date : 2020-03-31
Text Analysis With R written by Matthew L. Jockers and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-31 with Computers categories.
Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying. Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms.
Using Computational Text Analysis With Social Media Text
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Author : Justin T. Ho
language : en
Publisher:
Release Date : 2022
Using Computational Text Analysis With Social Media Text written by Justin T. Ho and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Computational linguistics categories.
This case study introduces a mixed-methods approach that combines qualitative textual analysis and computational text analysis. Following the advent of the internet and social media, a wide range of social and political phenomena have developed an online aspect. However, the vast volume of internet data renders many qualitative analysis methods infeasible. This approach provides a way to describe the general pattern within large text corpora and select a manageable subset for further analysis. The approach is applicable to a wide range of research that utilizes text data.
Text Analysis With R For Students Of Literature
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Author : Matthew Jockers
language : en
Publisher: Springer
Release Date : 2014-06-14
Text Analysis With R For Students Of Literature written by Matthew Jockers and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-14 with Computers categories.
Text Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying.
Natural Language Processing And Computational Linguistics
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Author : Bhargav Srinivasa-Desikan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-29
Natural Language Processing And Computational Linguistics written by Bhargav Srinivasa-Desikan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.
Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!
Text Analytics
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Author : Domenica Fioredistella Iezzi
language : en
Publisher: Springer
Release Date : 2020-11-25
Text Analytics written by Domenica Fioredistella Iezzi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Social Science categories.
Focusing on methodologies, applications and challenges of textual data analysis and related fields, this book gathers selected and peer-reviewed contributions presented at the 14th International Conference on Statistical Analysis of Textual Data (JADT 2018), held in Rome, Italy, on June 12-15, 2018. Statistical analysis of textual data is a multidisciplinary field of research that has been mainly fostered by statistics, linguistics, mathematics and computer science. The respective sections of the book focus on techniques, methods and models for text analytics, dictionaries and specific languages, multilingual text analysis, and the applications of text analytics. The interdisciplinary contributions cover topics including text mining, text analytics, network text analysis, information extraction, sentiment analysis, web mining, social media analysis, corpus and quantitative linguistics, statistical and computational methods, and textual data in sociology, psychology, politics, law and marketing.
Aspects Of Automatic Text Analysis
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Author : Alexander Mehler
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-24
Aspects Of Automatic Text Analysis written by Alexander Mehler and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-24 with Technology & Engineering categories.
The significance of natural language texts as the prime information structure for the management and dissemination of knowledge is - as the rise of the web shows - still increasing. Making relevant texts available in different contexts is of primary importance for efficient task completion in academic and industrial settings. Meeting this demand requires automatic form and content based processing of texts, which enables to reconstruct or even to explore the dynamic relationship of language system, text event and context type. The rise of new application areas, disciplines and methods (e.g. text and web mining) testify to the importance of this task. Moreover, the growing area of new media demands the further development of methods of text analysis with respect to their computational linguistic, information theoretical, and mathematical underpinning. This book contributes to this task. It collects contributions of authors from a multidisciplinary area who focus on the topic of automatic text analysis from several (i.e. linguistic, mathematical, and information theoretical) perspectives. It describes methodological as well as methodical foundations and collects approaches in the field of text and corpus linguistics. In this sense, it contributes to the computational linguistic and information theoretical grounding of automatic text analysis.
Research Anthology On Implementing Sentiment Analysis Across Multiple Disciplines
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2022-06-10
Research Anthology On Implementing Sentiment Analysis Across Multiple Disciplines written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Computers categories.
The rise of internet and social media usage in the past couple of decades has presented a very useful tool for many different industries and fields to utilize. With much of the world’s population writing their opinions on various products and services in public online forums, industries can collect this data through various computational tools and methods. These tools and methods, however, are still being perfected in both collection and implementation. Sentiment analysis can be used for many different industries and for many different purposes, which could better business performance and even society. The Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines discusses the tools, methodologies, applications, and implementation of sentiment analysis across various disciplines and industries such as the pharmaceutical industry, government, and the tourism industry. It further presents emerging technologies and developments within the field of sentiment analysis and opinion mining. Covering topics such as electronic word of mouth (eWOM), public security, and user similarity, this major reference work is a comprehensive resource for computer scientists, IT professionals, AI scientists, business leaders and managers, marketers, advertising agencies, public administrators, government officials, university administrators, libraries, students and faculty of higher education, researchers, and academicians.
Text Analysis With R
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Author : Matthew Lee Jockers
language : en
Publisher:
Release Date : 2020
Text Analysis With R written by Matthew Lee Jockers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computational linguistics categories.
This practical introduction explores core R procedures and processes and offers a thorough understanding of the possibilities of computational text analysis at both micro and macro scales. Each chapter concludes with a set of practice exercises.
The Bloomsbury Handbook To The Digital Humanities
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Author : James O’Sullivan
language : en
Publisher: Bloomsbury Publishing
Release Date : 2022-11-03
The Bloomsbury Handbook To The Digital Humanities written by James O’Sullivan and has been published by Bloomsbury Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-03 with Literary Criticism categories.
The Bloomsbury Handbook to the Digital Humanities reconsiders key debates, methods, possibilities, and failings from across the digital humanities, offering a timely interrogation of the present and future of the arts and humanities in the digital age. Comprising 43 essays from some of the field's leading scholars and practitioners, this comprehensive collection examines, among its many subjects, the emergence and ongoing development of DH, postcolonial digital humanities, feminist digital humanities, race and DH, multilingual digital humanities, media studies as DH, the failings of DH, critical digital humanities, the future of text encoding, cultural analytics, natural language processing, open access and digital publishing, digital cultural heritage, archiving and editing, sustainability, DH pedagogy, labour, artificial intelligence, the cultural economy, and the role of the digital humanities in climate change. The Bloomsbury Handbook to the Digital Humanities: Surveys key contemporary debates within DH, focusing on pressing issues of perspective, methodology, access, capacity, and sustainability. Reconsiders and reimagines the past, present, and future of the digital humanities. Features an intuitive structure which divides topics across five sections: “Perspectives & Polemics”, “Methods, Tools & Techniques”, “Public Digital Humanities”, “Institutional Contexts”, and “DH Futures”. Comprehensive in scope and accessibility written, this book is essential reading for students, scholars, and practitioners working across the digital humanities and wider arts and humanities. Featuring contributions from pre-eminent scholars and radical thinkers both established and emerging, The Bloomsbury Handbook to the Digital Humanities should long serve as a roadmap through the myriad formulations, methodologies, opportunities, and limitations of DH. Comprehensive in its scope, pithy in style yet forensic in its scholarship, this book is essential reading for students, scholars, and practitioners working across the digital humanities, whatever DH might be, and whatever DH might become.