Sentiment Analysis Techniques, Tools, Applications, and Challenge

Sentiment Analysis Techniques, Tools, Applications, and Challenge

Chitra A. Dhawale (P. R. Pote College of Engineering and Management, India) and Vandana V. Chaudhari (Smt. G. G. Khadse College, India)
DOI: 10.4018/978-1-5225-8575-6.ch003
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Sentiment (opinion) refers to the feelings of a human being, which are generally reflected through speech and writing in a particular natural language. The analysis of these sentiments are therefore carried with the help of natural language processing, text analysis, and computational linguistics to identify and extract subjective information in source materials. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing research, political reviews, policy making, decision making, customer service, etc. In this chapter the authors include the introduction to sentiment analysis, various approaches for classification of sentiment analysis, various tools used, the application areas, challenges, and future research direction in this most demanding area.
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Basics Of Sentiment Analysis

Sentiment analysis is the study of computing sentiments, opinions and emotions from the text. The primary goal of sentiment analysis is to detect the subjective information from text and define the mind set of author about point

Data Source

The data is obtained from following sources-


It’s easy to create the blogs that’s why people create the blog and uses this blog to share their opinion regarding any topics. We get a huge volume of data from the blogs.

Review Sites

Before purchasing any product firstly the user take the review of that product and a large number of reviews are available on Internet because the people share their opinion about any product that they used.


The multi-domain sentiment dataset is available. Most of the work and analysis is done on movie reviews; that movie reviews dataset is used for classification.


It is very popular communication tool on Internet. Daily millions of messages appear for micro-blogging such as Twitter, Facebook, and Tumbler etc. These messages sometimes used for classifying sentiment.

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