February 29, 2024Deleted JournalOpen Access

A Comparative Study on Machine Learning Approaches for Sentiment Analysis

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Authors

MKMunnangi Pranish KumarAmrita Vishwa Vidyapeetham TKT. KumaresanDr. N.G.P. Institute of Technology

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Implication

Comparative analysis demonstrates BERT classifier achieves superior accuracy in Amazon electronics reviews, suggesting transformer models outperform traditional machine learning.

Key Points

The BERT model achieves superior classification accuracy for sentiment analysis of product reviews, outperforming multiple traditional machine learning approaches.
Comparative evaluation assesses logistic regression, naive bayes classifier, random forest, and support vector machines across multi-paragraph customer electronics reviews.
Findings highlight that transformer-based sentiment analysis outperforms conventional machine learning algorithms on complex customer feedback in commercial recommendation systems.

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Kumar et al. (2024) studied this question.

synapsesocial.com/papers/68e77088b6db6435876e58ce https://doi.org/10.47392/irjaeh.2024.0029

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Implication

Comparative analysis demonstrates BERT classifier achieves superior accuracy in Amazon electronics reviews, suggesting transformer models outperform traditional machine learning.

A Comparative Study on Machine Learning Approaches for Sentiment Analysis

Discussion

Member takes

Implication

Key Points

Cite This Study

A Comparative Study on Machine Learning Approaches for Sentiment Analysis

Discussion

Member takes

Implication

Key Points

Cite This Study

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