Predictive analytics II CHAPTER Text. Web. and social Media analytics Learning Objectives for Chapter 5 Describe text analytics and understand the need for text mining Differentiate among text analytics, text mining, and data mining Understand the different application areas for text mining Know the process of carrying out a text mining project Appreciate the different methods to introduce structure to text-based data Describe sentiment analysi Develop familiarity with popular applications of sentiment analysis Learn the common methods for sentiment analysis Become familiar with speech analytics as it relates to sentiment analysis CHAPTER OVERVIE This chapter provides a comprehensive overview of text analytics/mining and Web analytics/mining along with their popular application areas such as search engines, sentiment analysis, and social network/media analytics. As we have been witnessing the recent years, the unstructured data generated over the Internet of things(Web, sensor networks, RFID-enabled supply chain systems, surveillance networkS, etc. )is increasing at an exponential pace, and there is no indication of its slowing down. This changing nature of data is forcing organizations to make text and Web analytics a critical part of heir business intelligence/analytics infrastructure Copyright C2018 Pearson Education, Inc.1 Copyright © 2018Pearson Education, Inc. Predictive Analytics II: Text, Web, and Social Media Analytics Learning Objectives for Chapter 5 ▪ Describe text analytics and understand the need for text mining ▪ Differentiate among text analytics, text mining, and data mining ▪ Understand the different application areas for text mining ▪ Know the process of carrying out a text mining project ▪ Appreciate the different methods to introduce structure to text-based data ▪ Describe sentiment analysis ▪ Develop familiarity with popular applications of sentiment analysis ▪ Learn the common methods for sentiment analysis ▪ Become familiar with speech analytics as it relates to sentiment analysis CHAPTER OVERVIEW This chapter provides a comprehensive overview of text analytics/mining and Web analytics/mining along with their popular application areas such as search engines, sentiment analysis, and social network/media analytics. As we have been witnessing in the recent years, the unstructured data generated over the Internet of things (Web, sensor networks, RFID-enabled supply chain systems, surveillance networks, etc.) is increasing at an exponential pace, and there is no indication of its slowing down. This changing nature of data is forcing organizations to make text and Web analytics a critical part of their business intelligence/analytics infrastructure. CHAPTER 5