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Tasks, Approaches, and Avenues of Opinion Mining, Sentiment Analysis, and Emotion Analysis: Opinion Mining and Extents
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Author(s): Amira M. Idrees (Faculty of Computers and Information Technology, Future University in Egypt, Egypt), Fatma Gamal Eldin (Faculty of Computers and Information Technology, Future University in Egypt, Egypt), Amr Mansour Mohsen (Faculty of Computers and Information Technology, Future University in Egypt, Egypt)and Hesham Ahmed Hassan (Faculty of Computers and Artificial Intelligence, Cairo University, Egypt)
Copyright: 2022
Pages: 39
Source title:
Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 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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