Abstract
Sentiment analysis or opinion mining is the computational study of people's opinions, sentiments, evaluations, attitudes, moods, and emotions. It is one of the most active research areas in natural language processing, data mining, information retrieval, and Web mining. In recent years, its research and applications have also spread to management sciences and social sciences due to its importance to business and society as a whole. This chapter defines the sentiment analysis problem and its related concepts such as sentiment, opinion, emotion, mood, and affect. The goal is to abstract a structure from the complex unstructured natural language text related to the problem and its pertinent concepts. The definitions not only enable us to see a rich set of inter-related sub-problems, but also a common framework that can unify existing research directions. They also help researchers design more robust solution techniques by exploiting the inter-relationships of the sub-problems.
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Liu, B. (2017). Many Facets of Sentiment Analysis. In: Cambria, E., Das, D., Bandyopadhyay, S., Feraco, A. (eds) A Practical Guide to Sentiment Analysis. Socio-Affective Computing, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-55394-8_2
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