Performance Evaluation of Machine Learning Algorithms in Aspect-Based Sentiment Analysis on E-Commerce User Reviews

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SVM achieved the highest accuracy of 89.3% in aspect-based sentiment analysis.
Random Forest, KNN, and Naïve Bayes followed, with accuracies of 87.1%, 84.6%, and 82.5%, respectively.
The research involves training models using 20,000 user reviews from e-commerce platforms Shopee and Tokopedia.
Findings highlight the effectiveness of machine learning in enhancing user experience in the growing e-commerce sector.

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This analysis evaluates machine learning algorithms' performance in processing user reviews, suggesting improved customer engagement strategies.

Pakpahan et al. (2025) studied this question.

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This analysis evaluates machine learning algorithms' performance in processing user reviews, suggesting improved customer engagement strategies.