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Tasks, Approaches, and Avenues of Opinion Mining, Sentiment Analysis, and Emotion Analysis: Opinion Mining and Extents

Tasks, Approaches, and Avenues of Opinion Mining, Sentiment Analysis, and Emotion Analysis: Opinion Mining and Extents

Amira M. Idrees, Fatma Gamal Eldin, Amr Mansour Mohsen, Hesham Ahmed Hassan
Copyright: © 2022 |Pages: 39
ISBN13: 9781668463031|ISBN10: 1668463032|EISBN13: 9781668463048
DOI: 10.4018/978-1-6684-6303-1.ch005
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MLA

Idrees, Amira M., et al. "Tasks, Approaches, and Avenues of Opinion Mining, Sentiment Analysis, and Emotion Analysis: Opinion Mining and Extents." Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines, edited by Information Resources Management Association, IGI Global, 2022, pp. 77-115. https://doi.org/10.4018/978-1-6684-6303-1.ch005

APA

Idrees, A. M., Eldin, F. G., Mohsen, A. M., & Hassan, H. A. (2022). Tasks, Approaches, and Avenues of Opinion Mining, Sentiment Analysis, and Emotion Analysis: Opinion Mining and Extents. In I. Management Association (Ed.), Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines (pp. 77-115). IGI Global. https://doi.org/10.4018/978-1-6684-6303-1.ch005

Chicago

Idrees, Amira M., et al. "Tasks, Approaches, and Avenues of Opinion Mining, Sentiment Analysis, and Emotion Analysis: Opinion Mining and Extents." In Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines, edited by Information Resources Management Association, 77-115. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-6303-1.ch005

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Abstract

Every successful business aims to know how customers feel about its brands, services, and products. People freely express their views, ideas, sentiments, and opinions on social media for their day-to-day activities, for product reviews, for surveys, and even for their public opinions. This process provides a fortune of valuable resources about the market for any type of business. Unfortunately, it's impossible to manually analyze this massive quantity of information. Sentiment analysis (SA) and opinion mining (OM), as new fields of natural language processing, have the potential benefit of analyzing such a huge amount of data. SA or OM is the computational treatment of opinions, sentiments, and subjectivity of text. This chapter introduces the reader to a survey of different text SA and OM proposed techniques and approaches. The authors discuss in detail various approaches to perform a computational treatment for sentiments and opinions with their strengths and drawbacks.

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