Multidimensional statistical analysis of textual data is a powerful technique that enables researchers to uncover deeper insights into the context and meaning of documents. This book addresses the challenge of jointly analyzing textual and contextual data, presenting rigorous theoretical foundations alongside practical methodologies. By incorporating metadata and contextual information, readers can extract richer, more nuanced information from textual corpora, making this book an essential resource for statisticians, data scientists, and linguistics experts.
The book explores a wide range of textual data, from open-ended survey responses and political speeches to legal texts, literary works, and technical reports. It also examines the diverse contextual variables that shape these texts, such as sociodemographic characteristics, chronology, political affiliations, and external influences. Through real-world examples, readers will learn how to apply exploratory multivariate statistical methods to compare, characterize, and reveal the underlying structure of textual data. Each chapter builds on the previous one, offering a systematic approach to encoding, analyzing, and visualizing textual and contextual data. Topics include machine learning methods like latent semantic analysis and correspondence analysis, clustering techniques, restricted clustering defined by contextual data, and advanced visualization tools. The book also introduces methodologies for analyzing multilingual corpora and isolated texts, emphasizing the importance of discourse strategies and thematic contrasts.
This book is not only a guide to advanced statistical methods but also a practical toolkit for researchers working with diverse corpora. Whether analyzing legal databases, sensory evaluations, or political speeches, readers will find robust techniques to uncover patterns, relationships, and strategies within their data. By combining textual and contextual analysis, this book empowers readers to make meaningful comparisons and draw actionable conclusions.
KEY FEATURES:
• Comprehensive coverage of methods for jointly analyzing textual and contextual data.
• Practical applications to diverse corpora, including legal texts, political speeches, and sensory evaluations.
• Systematic comparison of machine learning methods like latent semantic analysis and correspondence analysis.
• Advanced visualization techniques, including interactive, 3D, and animated graphics.
• Methodologies for analyzing multilingual corpora and isolated texts, with a focus on discourse strategies.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Dr. Mónica Bécue-Bertaut taught statistics and data science at the Universitat Politènica de Catalunya and offered numerous guest lectures on textual data science in different countries. She has published several books and chapters on this topic, and she has helped design software related to textual data science, including SPAD.T and the R package Xplortext. She is an elected fellow of the International Statistical Institute and a Chevalier des Palmes Académiques, a distinction bestowed by the French government.
Dr. Ramón Alvarez-Esteban is an associate professor at the University of León (Spain), where he teaches multivariate data analysis and R. His research interests include textual data analysis, climate change models, and integrated statistical and geospatial techniques. He is an author and the maintainer of the Xplortext R package (Statistical Analysis of Textual Data), which has been available on the CRAN website since 2017.
Multidimensional statistical analysis of textual data is a powerful technique that enables researchers to uncover deeper insights into the context and meaning of documents. This book addresses the challenge of jointly analyzing textual and contextual data, presenting rigorous theoretical foundations alongside practical methodologies.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. Multidimensional statistical analysis of textual data is a powerful technique that enables researchers to uncover deeper insights into the context and meaning of documents. This book addresses the challenge of jointly analyzing textual and contextual data, presenting rigorous theoretical foundations alongside practical methodologies. By incorporating metadata and contextual information, readers can extract richer, more nuanced information from textual corpora, making this book an essential resource for statisticians, data scientists, and linguistics experts.The book explores a wide range of textual data, from open-ended survey responses and political speeches to legal texts, literary works, and technical reports. It also examines the diverse contextual variables that shape these texts, such as sociodemographic characteristics, chronology, political affiliations, and external influences. Through real-world examples, readers will learn how to apply exploratory multivariate statistical methods to compare, characterize, and reveal the underlying structure of textual data. Each chapter builds on the previous one, offering a systematic approach to encoding, analyzing, and visualizing textual and contextual data. Topics include machine learning methods like latent semantic analysis and correspondence analysis, clustering techniques, restricted clustering defined by contextual data, and advanced visualization tools. The book also introduces methodologies for analyzing multilingual corpora and isolated texts, emphasizing the importance of discourse strategies and thematic contrasts.This book is not only a guide to advanced statistical methods but also a practical toolkit for researchers working with diverse corpora. Whether analyzing legal databases, sensory evaluations, or political speeches, readers will find robust techniques to uncover patterns, relationships, and strategies within their data. By combining textual and contextual analysis, this book empowers readers to make meaningful comparisons and draw actionable conclusions.KEY FEATURES: Comprehensive coverage of methods for jointly analyzing textual and contextual data. Practical applications to diverse corpora, including legal texts, political speeches, and sensory evaluations. Systematic comparison of machine learning methods like latent semantic analysis and correspondence analysis. Advanced visualization techniques, including interactive, 3D, and animated graphics. Methodologies for analyzing multilingual corpora and isolated texts, with a focus on discourse strategies. Multidimensional statistical analysis of textual data is a powerful technique that enables researchers to uncover deeper insights into the context and meaning of documents. This book addresses the challenge of jointly analyzing textual and contextual data, presenting rigorous theoretical foundations alongside practical methodologies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032502267
Quantité disponible : 1 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9781032502267
Quantité disponible : Plus de 20 disponibles
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. Multidimensional statistical analysis of textual data is a powerful technique that enables researchers to uncover deeper insights into the context and meaning of documents. This book addresses the challenge of jointly analyzing textual and contextual data, presenting rigorous theoretical foundations alongside practical methodologies. By incorporating metadata and contextual information, readers can extract richer, more nuanced information from textual corpora, making this book an essential resource for statisticians, data scientists, and linguistics experts.The book explores a wide range of textual data, from open-ended survey responses and political speeches to legal texts, literary works, and technical reports. It also examines the diverse contextual variables that shape these texts, such as sociodemographic characteristics, chronology, political affiliations, and external influences. Through real-world examples, readers will learn how to apply exploratory multivariate statistical methods to compare, characterize, and reveal the underlying structure of textual data. Each chapter builds on the previous one, offering a systematic approach to encoding, analyzing, and visualizing textual and contextual data. Topics include machine learning methods like latent semantic analysis and correspondence analysis, clustering techniques, restricted clustering defined by contextual data, and advanced visualization tools. The book also introduces methodologies for analyzing multilingual corpora and isolated texts, emphasizing the importance of discourse strategies and thematic contrasts.This book is not only a guide to advanced statistical methods but also a practical toolkit for researchers working with diverse corpora. Whether analyzing legal databases, sensory evaluations, or political speeches, readers will find robust techniques to uncover patterns, relationships, and strategies within their data. By combining textual and contextual analysis, this book empowers readers to make meaningful comparisons and draw actionable conclusions.KEY FEATURES: Comprehensive coverage of methods for jointly analyzing textual and contextual data. Practical applications to diverse corpora, including legal texts, political speeches, and sensory evaluations. Systematic comparison of machine learning methods like latent semantic analysis and correspondence analysis. Advanced visualization techniques, including interactive, 3D, and animated graphics. Methodologies for analyzing multilingual corpora and isolated texts, with a focus on discourse strategies. Multidimensional statistical analysis of textual data is a powerful technique that enables researchers to uncover deeper insights into the context and meaning of documents. This book addresses the challenge of jointly analyzing textual and contextual data, presenting rigorous theoretical foundations alongside practical methodologies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781032502267
Quantité disponible : 1 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. N° de réf. du vendeur 408877680
Quantité disponible : 3 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Hardback. Etat : New. New copy - Usually dispatched within 4 working days. N° de réf. du vendeur B9781032502267
Quantité disponible : 1 disponible(s)
Vendeur : Books Puddle, Woodside, NY, Etats-Unis
Etat : New. N° de réf. du vendeur 26405357999
Quantité disponible : 3 disponible(s)
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L1-9781032502267
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
HRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du vendeur L1-9781032502267
Quantité disponible : Plus de 20 disponibles
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. N° de réf. du vendeur 18405357989
Quantité disponible : 3 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. N° de réf. du vendeur 2785644401
Quantité disponible : Plus de 20 disponibles