Machine Learning Based Review Analysis of Electronic Appliances

Abstract

Sentiment Analysis and Opinion Mining have emerged as highly popular fields for analyzing and extracting valuable information from textual data sourced from diverse platforms like Facebook, Twitter, and Amazon. These techniques hold a crucial role in  impowering businesses to actively enhance their strategies by gaining comprehensive insights into customers' feedback regarding their products. The process involves leveraging computational methods to study individuals’ buying behavior and subsequently mining their opinions about a company’s business entity, which could manifest as an event, individual, blog post, or product experience. This paper focuses on utilizing a dataset obtained from Amazon, comprising reviews spanning various product categories such as laptops, cameras and mobile phones. Following data preprocessing, we employ machine learning
algorithms to classify the reviews as either positive or negative sentiment. This classification step enables us to analyze the overall sentiment associated with the products and draw meaningful conclusions.