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Automated Sentiment Analysis Of Product Reviews Using Machine Learning Techniques

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Analysis using sentiment analysis identifies positive, negative, and neutral reviews in e-commerce, suggesting effective customer insights.

Sentiment analysis identified review sentiments with accuracy, enhancing decision-making in e-commerce.
The model evaluation showed improved performance metrics, including accuracy and F1-score compared to traditional methods.
Data preprocessing steps like tokenization and stop word removal were integral for effective sentiment categorization.
Findings highlight the importance of automated sentiment analysis in boosting consumer confidence in product choices.

Sharma et al. (2025) studied this question.

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Analysis using sentiment analysis identifies positive, negative, and neutral reviews in e-commerce, suggesting effective customer insights.