Aspect-Based Sentiment Analysis of After-Sales Service Quality: A Case Study of Snowa and Competitors Using Digikala Reviews

Abstract

In recent years, aspect-based sentiment analysis has gained attention as a method for processing and summarizing customer reviews. This type of analysis aims to answer two main questions: First, which aspect of the product is the review referring to? Second, what is the customer’s sentiment towards that aspect? Given the importance of after-sales service quality in customer satisfaction, this study examines an aspect-based analysis of a set of reviews from Digikala regarding the after-sales service quality of three washing machine brands, including Snowa and its two competitors. Deep learning models are implemented and evaluated based on example-based and label-based metrics. At the end, an analysis is conducted on customer satisfaction with the quality of after-sales services for the three selected brands. © 2024 IEEE.