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1. Explain the relationship among data mining, text mining, and sentiment analysis.
2. In your own words, define text mining, and discuss its most popular applications.
3. What does it mean to induce structure into text-based data? Discuss the alternative ways of inducing structure into them.
4. What is the role of NLP in text mining? Discuss the capabilities and limitations of NLP in the context of text mining.
5. Explore the sections on applications as well as software. Find names of at least three.
6. Browse the Web and your library's digital databases to identify articles that make the linkage between text/Web mining and contemporary business intelligence systems.
7. What are the common challenges with which sentiment analysis deals? What are the most popular application areas for sentiment analysis? Why?
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