Sentiment Analysis of Amazon Product Reviews using Supervised Machine Learning Techniques

Naveed Sultan

doi:10.17977/um018v5i12022p101-108

Sentiment Analysis of Amazon Product Reviews using Supervised Machine Learning Techniques

Naveed Sultan

Abstract

Today, everything is sold online, and many individuals can post reviews about different products to show feedback. Serves as feedback for businesses regarding buyer reviews, performance, product quality, and seller service. The project focuses on buyer opinions based on Mobile Phone reviews. Sentiment analysis is the function of analyzing all these data, obtaining opinions about these products and services that classify them as positive, negative, or neutral. This insight can help companies improve their products and help potential buyers make the right decisions. Once the preprocessing is classified on a trained dataset, these reviews must be preprocessed to remove unwanted data such as stop words, verbs, pos tagging, punctuation, and attachments. Many techniques are present to perform such tasks, but in this article, we will use a model that will use different inspection machine techniques.

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DOI: http://dx.doi.org/10.17977/um018v5i12022p101-108