Book Reviews Sentiment Classifier

Book Reviews Sentiment Classifier

This model is created to categorize the positive or negative sentiment of any book reader's evaluation of that book.

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Positive: A positive label indicates that readers are expressing their happiness and satisfaction.
Negative: A negative label indicates conversations in that readers express their dissatisfaction, rage, disappointment or simply sadness.




In this digital age, people are much more interested in buying and selling things on e-commerce websites. The book is one of the best selling items online by different online stores. Amazon is one of the leading online stores with a rich assortment of products, processing million-dollar transactions every year. The book, in particular, is one of Amazon's bestsellers. That's why Sentiment has a very strong position in market analysis and future business development. Based on sentiment, it is now possible to predict anything business related based on the user and other NLP-related areas where the ideas come from. This model focuses on determining the quality of books as well as authors through user-provided review comments and rating analysis. Thus, people can find the best book they need in a short time and without difficulty.

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Designed for marketing and research professionals. No programming skills are required.

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