Computational Text Analysis

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Computational Text Analysis

Soumya Raychaudhuri
Computational Text Analysis Book PDF

Author : Soumya Raychaudhuri
Publisher : OUP Oxford
Page : 312 pages
File Size : 44,5 Mb
Release : 2006-01-26
Category : Science
ISBN : 9780191513770

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Computational Text Analysis by Soumya Raychaudhuri Pdf

This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply. impossible. Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically read the literature on all the genes. Including background chapters on the necessary biology, statistics and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science

Computational Analysis of Communication

Wouter van Atteveldt,Damian Trilling,Carlos Arcila Calderon
Computational Analysis of Communication Book PDF

Author : Wouter van Atteveldt,Damian Trilling,Carlos Arcila Calderon
Publisher : John Wiley & Sons
Page : 341 pages
File Size : 41,5 Mb
Release : 2022-03-02
Category : Social Science
ISBN : 9781119680239

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Computational Analysis of Communication by Wouter van Atteveldt,Damian Trilling,Carlos Arcila Calderon Pdf

Provides clear guidance on leveraging computational techniques to answer social science questions In disciplines such as political science, sociology, psychology, and media studies, the use of computational analysis is rapidly increasing. Statistical modeling, machine learning, and other computational techniques are revolutionizing the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and much more. Computational Analysis of Communication teaches social science students and practitioners how computational methods can be used in a broad range of applications, providing discipline-relevant examples, clear explanations, and practical guidance. Assuming little or no background in data science or computer linguistics, this accessible textbook teaches readers how to use state-of-the art computational methods to perform data-driven analyses of social science issues. A cross-disciplinary team of authors—with expertise in both the social sciences and computer science—explains how to gather and clean data, manage textual, audio-visual, and network data, conduct statistical and quantitative analysis, and interpret, summarize, and visualize the results. Offered in a unique hybrid format that integrates print, ebook, and open-access online viewing, this innovative resource: Covers the essential skills for social sciences courses on big data, data visualization, text analysis, predictive analytics, and others Integrates theory, methods, and tools to provide unified approach to the subject Includes sample code in Python and links to actual research questions and cases from social science and communication studies Discusses ethical and normative issues relevant to privacy, data ownership, and reproducible social science Developed in partnership with the International Communication Association and by the editors of Computational Communication Research Computational Analysis of Communication is an invaluable textbook and reference for students taking computational methods courses in social sciences, and for professional social scientists looking to incorporate computational methods into their work.

Mapping Texts

Dustin S. Stoltz,Marshall A. Taylor
Mapping Texts Book PDF

Author : Dustin S. Stoltz,Marshall A. Taylor
Publisher : Oxford University Press
Page : 326 pages
File Size : 47,5 Mb
Release : 2024-02-15
Category : Qualitative research
ISBN : 9780197756881

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Mapping Texts by Dustin S. Stoltz,Marshall A. Taylor Pdf

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.

Clinical Text Mining

Hercules Dalianis
Clinical Text Mining Book PDF

Author : Hercules Dalianis
Publisher : Springer
Page : 192 pages
File Size : 47,9 Mb
Release : 2018-05-14
Category : Computers
ISBN : 9783319785035

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Clinical Text Mining by Hercules Dalianis Pdf

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Text Analysis with R

Matthew L. Jockers,Rosamond Thalken
Text Analysis with R Book PDF

Author : Matthew L. Jockers,Rosamond Thalken
Publisher : Springer
Page : 277 pages
File Size : 43,9 Mb
Release : 2020-03-31
Category : Computers
ISBN : 3030396428

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Text Analysis with R by Matthew L. Jockers,Rosamond Thalken Pdf

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.

Text Analysis with R

Matthew L. Jockers,Rosamond Thalken
Text Analysis with R Book PDF

Author : Matthew L. Jockers,Rosamond Thalken
Publisher : Springer Nature
Page : 277 pages
File Size : 53,9 Mb
Release : 2020-03-30
Category : Computers
ISBN : 9783030396435

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Text Analysis with R by Matthew L. Jockers,Rosamond Thalken Pdf

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.

Text Mining with R

Julia Silge,David Robinson
Text Mining with R Book PDF

Author : Julia Silge,David Robinson
Publisher : "O'Reilly Media, Inc."
Page : 193 pages
File Size : 48,7 Mb
Release : 2017-06-12
Category : Computers
ISBN : 9781491981627

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Text Mining with R by Julia Silge,David Robinson Pdf

Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.

Natural Language Processing and Computational Linguistics

Bhargav Srinivasa-Desikan
Natural Language Processing and Computational Linguistics Book PDF

Author : Bhargav Srinivasa-Desikan
Publisher : Packt Publishing Ltd
Page : 298 pages
File Size : 48,8 Mb
Release : 2018-06-29
Category : Computers
ISBN : 9781788837033

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Natural Language Processing and Computational Linguistics by Bhargav Srinivasa-Desikan Pdf

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 as Data

Justin Grimmer,Margaret E. Roberts,Brandon M. Stewart
Text as Data Book PDF

Author : Justin Grimmer,Margaret E. Roberts,Brandon M. Stewart
Publisher : Princeton University Press
Page : 360 pages
File Size : 55,6 Mb
Release : 2022-03-29
Category : Computers
ISBN : 9780691207551

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Text as Data by Justin Grimmer,Margaret E. Roberts,Brandon M. Stewart Pdf

A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry

Supervised Machine Learning for Text Analysis in R

Emil Hvitfeldt,Julia Silge
Supervised Machine Learning for Text Analysis in R Book PDF

Author : Emil Hvitfeldt,Julia Silge
Publisher : CRC Press
Page : 402 pages
File Size : 46,6 Mb
Release : 2021-10-22
Category : Computers
ISBN : 9781000461978

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Supervised Machine Learning for Text Analysis in R by Emil Hvitfeldt,Julia Silge Pdf

Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.

Text Analysis with R for Students of Literature

Matthew Jockers
Text Analysis with R for Students of Literature Book PDF

Author : Matthew Jockers
Publisher : Springer
Page : 194 pages
File Size : 47,8 Mb
Release : 2014-06-14
Category : Computers
ISBN : 3319031651

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Text Analysis with R for Students of Literature by Matthew Jockers Pdf

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.

Applied Text Analysis with Python

Benjamin Bengfort,Rebecca Bilbro,Tony Ojeda
Applied Text Analysis with Python Book PDF

Author : Benjamin Bengfort,Rebecca Bilbro,Tony Ojeda
Publisher : "O'Reilly Media, Inc."
Page : 332 pages
File Size : 54,7 Mb
Release : 2018-06-11
Category : Computers
ISBN : 9781491962992

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Applied Text Analysis with Python by Benjamin Bengfort,Rebecca Bilbro,Tony Ojeda Pdf

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity

Text Mining for Qualitative Data Analysis in the Social Sciences

Gregor Wiedemann
Text Mining for Qualitative Data Analysis in the Social Sciences Book PDF

Author : Gregor Wiedemann
Publisher : Springer
Page : 294 pages
File Size : 50,9 Mb
Release : 2016-08-23
Category : Social Science
ISBN : 9783658153090

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Text Mining for Qualitative Data Analysis in the Social Sciences by Gregor Wiedemann Pdf

Gregor Wiedemann evaluates text mining applications for social science studies with respect to conceptual integration of consciously selected methods, systematic optimization of algorithms and workflows, and methodological reflections relating to empirical research. In an exemplary study, he introduces workflows to analyze a corpus of around 600,000 newspaper articles on the subject of “democratic demarcation” in Germany. He provides a valuable resource for innovative measures to social scientists and computer scientists in the field of applied natural language processing.

Macroanalysis

Matthew L. Jockers
Macroanalysis Book PDF

Author : Matthew L. Jockers
Publisher : University of Illinois Press
Page : 211 pages
File Size : 46,7 Mb
Release : 2013-04-15
Category : Computers
ISBN : 9780252094767

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Macroanalysis by Matthew L. Jockers Pdf

In this volume, Matthew L. Jockers introduces readers to large-scale literary computing and the revolutionary potential of macroanalysis--a new approach to the study of the literary record designed for probing the digital-textual world as it exists today, in digital form and in large quantities. Using computational analysis to retrieve key words, phrases, and linguistic patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the "close-reading" of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections.

Computational Intelligence Applications for Text and Sentiment Data Analysis

Dipankar Das,Anup Kumar Kolya,Abhishek Basu,Soham Sarkar
Computational Intelligence Applications for Text and Sentiment Data Analysis Book PDF

Author : Dipankar Das,Anup Kumar Kolya,Abhishek Basu,Soham Sarkar
Publisher : Academic Press
Page : 272 pages
File Size : 48,8 Mb
Release : 2023-07-14
Category : Computers
ISBN : 9780323906371

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Computational Intelligence Applications for Text and Sentiment Data Analysis by Dipankar Das,Anup Kumar Kolya,Abhishek Basu,Soham Sarkar Pdf

Approx.330 pages Approx.330 pages