Analytical Review on Techniques and Challenges in Sentiment Analysis

Author:

Sagnika Santwana1,Das Nilanjana1,Pandey Swastika1,Bilgaiyan Saurabh1

Affiliation:

1. Kalinga Institute of Industrial Technology (Deemed), Bhubaneswar, India

Abstract

Opinion mining and sentiment analysis help in extracting valuable information from the huge user data generated in the form of opinions and reviews from the customers and comments. Such a huge increase in data available on the electronic or social media has also increased interest in this field. Sentiment analysis helps in extraction of opinions of others (writer or speaker) from a given source (text) using different methods and techniques like NLP, text mining, and linguistic computation and classifying them into positive, negative, and neutral opinions. Decision making for both consumers as well as the seller becomes much easier with such type of classification. This chapter consists of survey report on different elements of sentiment analysis, its applications, and challenges involved. The chapter studies and compares some of the techniques used to evaluate the item's reputation using sentiment analysis. A number of tools and features for sentiment analysis are also included in this chapter that can later help to perform better sentiment analysis of data.

Publisher

IGI Global

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