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Sentiment analysis applied on Amazon reviews
- 1 Faculty of Science, The University of Hong Kong, Hong Kong, 999077, Hong Kong China
- 2 Faculty of Science and Technology, Beijing Normal University-Hong Kong Baptist University United International College, Zhu hai, 519087, China
- 3 Faculty of Science and Technology, Beijing Normal University-Hong Kong Baptist University United International College, Zhu hai, 519087, China
* Author to whom correspondence should be addressed.
Abstract
With the rapid growth of e-commerce, accurately capturing buyers' sentiments through their reviews is increasingly vital for online marketplaces. In this paper, we aim to deal with sentiment analysis in these reviews by exploring effective methods to analyze them. We use a review dataset containing user ratings and comments on Amazon products. Applying the two-step methodology of data preprocessing and model building, we intend to employ models like LSTM and SVM to analyze Amazon customer reviews and gain insights into their performance. The findings of this study may also allow e-commerce platforms to provide better service to sellers and buyers.
Keywords
Sentiment Analysis, Amazon, e-commerce
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Cite this article
Li,J.;Pan,Q.;Wang,Y. (2024). Sentiment analysis applied on Amazon reviews. Applied and Computational Engineering,44,26-32.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation
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