Discussion (Chapter 7): What are the common challenges with which sentiment analysis deals? What are the most popular application areas for sentiment analysis? Why?
Questions for Discussions:
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.
Exercise: Go to teradatauniversitynetwork.com and find the case study named “eBay Analytics.” Read the case carefully and extend your understanding of it by searching the Internet for additional information, and answer the case questions.
Internet exercise: Go to kdnuggets.com. Explore the sections on applications as well as software. Find the names of at least three additional packages for data mining and text mining.
Questions for Discussions:
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.
Exercise: Go to teradatauniversitynetwork.com and find the case study named “eBay Analytics.” Read the case carefully and extend your understanding of it by searching the Internet for additional information, and answer the case questions.
Internet exercise: Go to kdnuggets.com. Explore the sections on applications as well as software. Find the names of at least three additional packages for data mining and text mining.
