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12 Contents

Academic Applications 335
▶ ApplicAtion cAse 7.4 Text Mining and Sentiment Analysis Help
Improve Customer Service Performance 336
7.5 Text Mining Process 337
Task 1: Establish the Corpus 338
Task 2: Create the Term–Document Matrix 339
Task 3: Extract the Knowledge 342
▶ ApplicAtion cAse 7.5 Research Literature Survey with Text
Mining 344
7.6 Text Mining Tools 347
Commercial Software Tools 347
Free Software Tools 347
▶ ApplicAtion cAse 7.6 A Potpourri of Text Mining Case Synopses 348
7.7 Sentiment Analysis Overview 349
▶ ApplicAtion cAse 7.7 Whirlpool Achieves Customer Loyalty and
Product Success with Text Analytics 351
7.8 Sentiment Analysis Applications 353
7.9 Sentiment Analysis Process 355
Methods for Polarity Identification 356
Using a Lexicon 357
Using a Collection of Training Documents 358
Identifying Semantic Orientation of Sentences and Phrases 358
Identifying Semantic Orientation of Document 358
7.10 Sentiment Analysis and Speech Analytics 359
How Is It Done? 359
▶ ApplicAtion cAse 7.8 Cutting Through the Confusion: Blue Cross
Blue Shield of North Carolina Uses Nexidia’s Speech Analytics to Ease
Member Experience in Healthcare 361
Chapter Highlights 363 • Key Terms 363
Questions for Discussion 364 • Exercises 364
▶ end-of-chApter ApplicAtion cAse BBVA Seamlessly Monitors
and Improves Its Online Reputation 365
References 366
Chapter 8 Web Analytics, Web Mining, and social Analytics 368
8.1 Opening Vignette: Security First Insurance Deepens
Connection with Policyholders 369
8.2 Web Mining Overview 371
8.3 Web Content and Web Structure Mining 374
▶ ApplicAtion cAse 8.1 Identifying Extremist Groups with Web Link
and Content Analysis 376
8.4 Search Engines 377
Anatomy of a Search Engine 377
1. Development Cycle 378
Web Crawler 378
Document Indexer 378

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