Abstract
Sentiment Analysis is a novel and broad area of Natural Language Processing (NLP) aiming to understand people’s sentiments and opinions about a given topic. In particular, this chapter focuses on the application of Sentiment Analysis to automatically evaluate online products and services reviews. Undoubtedly, the information in customer reviews is of great interest to both companies and consumers. Companies and organizations spend a huge amount of money to find customers’ opinions and sentiments, since this information is useful to exploit their marketing-mix in order to affect consumer satisfaction. Individuals are interested in others’ experiences when purchasing a product or hiring a service. Moreover, online opinions clearly influence the companies’ reputation. For this reason, Sentiment Analysis is expected to become a key component of Customer Relationship Management (CRM) solutions. However, the task of mining opinions in text, as any other NLP task, is a very challenging one. The objective of this chapter is to present the reader the main ideas of Sentiment Analysis and its practical applications in business intelligence. It also discussed the approaches and techniques used so far, and the corpora and resources most widely used in the development of sentiment-driven systems.
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