Feature-level Rating System using Customer Reviews and Review Votes

TL;DR

This paper develops a feature-level rating system for mobile products based on customer reviews and votes, providing detailed insights into specific features to aid manufacturers and consumers in decision making.

Contribution

It introduces a novel approach to derive feature-specific ratings from reviews and votes, enabling personalized and more informative product assessments.

Findings

Rated 108 features across 4,000+ mobiles from Amazon.

Enabled feature-focused sentiment analysis for detailed ratings.

Facilitated improved decision making for manufacturers and consumers.

Abstract

This work studies how we can obtain feature-level ratings of the mobile products from the customer reviews and review votes to influence decision making, both for new customers and manufacturers. Such a rating system gives a more comprehensive picture of the product than what a product-level rating system offers. While product-level ratings are too generic, feature-level ratings are particular; we exactly know what is good or bad about the product. There has always been a need to know which features fall short or are doing well according to the customer's perception. It keeps both the manufacturer and the customer well-informed in the decisions to make in improving the product and buying, respectively. Different customers are interested in different features. Thus, feature-level ratings can make buying decisions personalized. We analyze the customer reviews collected on an online shopping site (Amazon) about various mobile products and the review votes. Explicitly, we carry out a feature-focused sentiment analysis for this purpose. Eventually, our analysis yields ratings to 108 features for 4k+ mobiles sold online. It helps in decision making on how to improve the product (from the manufacturer's perspective) and in making the personalized buying decisions (from the buyer's perspective) a possibility. Our analysis has applications in recommender systems, consumer research, etc.