Sentiment Analysis of Amazon reviews with Natural Language Processing using Machine Learning Algorithms

<p>Sentiment analysis utilises natural language processing (NLP) techniques to create software that interprets text similarly to human comprehension. Sentiment analysis is a crucial business intelligence tool that allows organisations to improve products and services by analysing digital text to determine the author's viewpoint on a subject. This information is employed to augment customer service and elevate brand reputation. Naive Bayes, Support Vector Machines, and Logistic Regression are commonly utilised in sentiment analysis to predict sentiment in Amazon reviews by analysing textual features and training the model on labelled data. These models aid organisations in understanding customer satisfaction, enabling data-driven decision-making, and leveraging the extensive collection of Amazon reviews to foster corporate growth and success. The primary objective of this study was to conduct a thorough examination of the sentiments expressed in Amazon reviews for a variety of product categories.</p>

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-01
DOI
https://doi.org/10.5281/zenodo.16894928
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Sentiment Analysis of Amazon reviews with Natural Language Processing using Machine Learning Algorithms

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Sentiment Analysis of Amazon reviews with Natural Language Processing using Machine Learning Algorithms

article en

Abstract

<p>Sentiment analysis utilises natural language processing (NLP) techniques to create software that interprets text similarly to human comprehension. Sentiment analysis is a crucial business intelligence tool that allows organisations to improve products and services by analysing digital text to determine the author's viewpoint on a subject. This information is employed to augment customer service and elevate brand reputation. Naive Bayes, Support Vector Machines, and Logistic Regression are commonly utilised in sentiment analysis to predict sentiment in Amazon reviews by analysing textual features and training the model on labelled data. These models aid organisations in understanding customer satisfaction, enabling data-driven decision-making, and leveraging the extensive collection of Amazon reviews to foster corporate growth and success. The primary objective of this study was to conduct a thorough examination of the sentiments expressed in Amazon reviews for a variety of product categories.</p>

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 51%
Geochemistry and Geologic Mapping
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