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Paper Details


Title
Sentiment Analysis of Amazon Book Review Data Using Lexicon Based Analysis
Author
Fatema Khatun, Sheikh Abujar, SK. Fazlee Rabby, S. M. Mazharul Hoque Chowdhury, Syed Akhter Hossain, Zerin Nasrin Tumpa,
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Abstract

In this digital era, people are much more interested to buy and sell things in E-Commerce websites. Book is one of the mostly sold products on online by different online stores. Amazon is one of the leading online stores, which has million dollar transactions every year with its rich variety of products. In particular, book is one of the best-selling products of Amazon. Sentiment is therefore holding a very strong position in market analysis and future business development. Based on sentiment now it is possible to predict everything about business based on the user and other NLP related fields where opinion comes from someone. This research focuses on determining the quality of books as well as authors through the analysis of review comments and rating provided by the user. To determine that, lexicon based analysis is used here and using bag of word, the positivity and negativity of the review was determined. So that people can find the best book they need within a short time and without facing difficulty.

Keywords
Lexicon, Amazon, Online book reviews, Polarity, Sentiment analysis >
Journal or Conference Name
Advances in Intelligent Systems and Computing
Publication Year
2020
Indexing
scopus