Aspect-Based Sentiment Analysis of After-Sales Service Quality: A Case Study of Snowa and Competitors Using Digikala Reviews
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.
Authors
- Marjan Kaedi (ORCID: https://orcid.org/0000-0003-2000-4781)
- Safiyeh Samadanian
Institutions
- University of Isfahan (IR)
Publication Details
- Published
- 2024-12-24
- DOI
- https://doi.org/10.1109/ikt65497.2024.10892728
- Citations
- 1
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.35