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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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.
Labels
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.
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About Industry-specific Models

  • Industry-Specific AI Models are pre-trained classifiers built using labeled customer feedback from a specific sector. They help businesses analyze and categorize feedback with high accuracy, without requiring any manual setup.

  • Yes! You can create custom AI models tailored to your needs. Simply upload a training dataset with your own labels, build the model, and start analyzing feedback—all without writing a single line of code.

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  • Yes! You can enter a custom text in our console to see real-time classification results from any of our pre-trained AI models.

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