JOURNAL ARTICLE

Sentiment Analysis of Amazon Customer Product Reviews: A Review

Tayybaha Quyyam, Dr. Hamid Ghous

Year: 2021 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Internet is an easy way to for the customer to exchange information about the product over the shopping websites. It is important for the Shopping websites to understand the sentiment of the customer’s reviews. Sentiment Analysis is a type of natural language processing that can be used to understand the sentiments of customer reviews from the online platform such as Amazon. Sentiment analysis is also used for the client reviews which contain the type of texts, words, expressions, and star rating techniques. Sentiment analysis of the customer reviews can increase the sale of products. A variety of research has already been conducted related to the sentiment analysis using machine learning and deep learning methods. In this paper, we have analysed the literature related to sentiment analysis of customers’ reviews on Amazon based on Machine learning and Deep learning methods. We have also discussed the limitations of related literature and suggested new directions for future researchers.

Keywords:
Sentiment analysis Variety (cybernetics) Product (mathematics) The Internet Amazon rainforest Deep learning

Metrics

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Cited By
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FWCI (Field Weighted Citation Impact)
0
Refs
0.37
Citation Normalized Percentile
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Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Internet of Things and AI
Physical Sciences →  Computer Science →  Information Systems
Stock Market Forecasting Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research

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