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Chapter 1. Introduction to Text Analytics
Chapter 2. Fundamentals of Content Analysis
Chapter 3. Text Analytics Roadmap
Chapter 4. Text Pre-Processing
Chapter 5. Term-Document Representation
Chapter 6. Semantic Space Representation and Latent Semantic Analysis
Chapter 7. Cluster Analysis: Modeling Groups in Text
Chapter 8. Probabilistic Topic Models
Chapter 9. Classification Analysis: Machine Learning Applied to Text
Chapter 10. Modeling Text Sentiment: Learning and Lexicon Models
Chapter 11. Storytelling Using Text Data
Chapter 12. Visualizing Results
Chapter 13. Sentiment Analysis of Movie Reviews using R
Chapter 14. Latent Semantic Analysis (LSA) in Python
Chapter 15. Learning-Based Sentiment Analysis using RapidMiner
Chapter 16. SAS Visual Text Analytics.

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