Volume - 5 | Issue - 1 | march 2023
DOI
10.36548/jitdw.2023.1.006
Published
11 May, 2023
Digital reviews now have a significant impact on how consumers communicate globally and the effect of review on online purchases. Sentiment analysis is one of most common field for analysing and extracting information from data of text format from multiple platforms like Facebook, Amazon, Twitter, and others. This research aims to discuss and analyse the sentiments stated in Amazon product reviews using Support Vector Machine (SVM), Naive Bayes, Random Forest, and Decision Tree algorithms. The machine learning algorithms classify reviews as positive or negative. The performance of the algorithms is evaluated in terms of metrics such as accuracy, precision, recall and F score. As per the validated results, SVM performs better on accuracy rate compared to the other algorithms.
KeywordsMachine learning Product review Support Vector Machine Performance Metrics