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 cluster
analysis 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.