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

Authors :

Safiyeh Samadanian¹ Marjan Kaedi²

1- دانشگاه اصفهان/گروه صنعتی انتخاب الکترونیک آرمان 2- دانشگاه اصفهان

Keywords :

After-Sales Service،Aspect-Based Sentiment Analysis،Deep Learning،Multi-Label Classification

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.

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