Ebook: Exploring Textual Data

Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts.
Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and clusteranalysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided.

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Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts.
Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and clusteranalysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided.

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Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts.
Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and clusteranalysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided.
Content:
Front Matter....Pages i-xi
Introduction....Pages 1-3
Textual Statistics Scope and Applications....Pages 5-20
The Units of Textual Statistics....Pages 21-43
Correspondence Analysis of Lexical Tables....Pages 45-79
Cluster Analysis of Words and Texts....Pages 81-100
Visualization of Textual Data....Pages 101-128
Characteristic Textual Units, Modal Responses and Modal Texts....Pages 129-145
Longitudinal Partitions, Textual Time Series....Pages 147-162
Textual Discriminant Analysis....Pages 163-199
Back Matter....Pages 200-247

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Researchers in a number of disciplines deal with large text sets requiring both text management and text analysis. Faced with a large amount of textual data collected in marketing surveys, literary investigations, historical archives and documentary data bases, these researchers require assistance with organizing, describing and comparing texts.
Exploring Textual Data demonstrates how exploratory multivariate statistical methods such as correspondence analysis and clusteranalysis can be used to help investigate, assimilate and evaluate textual data. The main text does not contain any strictly mathematical demonstrations, making it accessible to a large audience. This book is very user-friendly with proofs abstracted in the appendices. Full definitions of concepts, implementations of procedures and rules for reading and interpreting results are fully explored. A succession of examples is intended to allow the reader to appreciate the variety of actual and potential applications and the complementary processing methods. A glossary of terms is provided.
Content:
Front Matter....Pages i-xi
Introduction....Pages 1-3
Textual Statistics Scope and Applications....Pages 5-20
The Units of Textual Statistics....Pages 21-43
Correspondence Analysis of Lexical Tables....Pages 45-79
Cluster Analysis of Words and Texts....Pages 81-100
Visualization of Textual Data....Pages 101-128
Characteristic Textual Units, Modal Responses and Modal Texts....Pages 129-145
Longitudinal Partitions, Textual Time Series....Pages 147-162
Textual Discriminant Analysis....Pages 163-199
Back Matter....Pages 200-247
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