# Multi-Class Sentiment Analysis with E-Commerce User Reviews: Comparisons of Classical and Deep Learning Applications

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/multi-class-sentiment-analysis-with-e-commerce-user-reviews-comparisons-of/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yusuf Can Simsek,Mehmet Buğra Balci,Mehmet Arzu,Mahmut Kaya,Yunus Santur |
| Citations | 1 |
| DOI | 10.1109/idap68205.2025.11222169 |
| Fields | Computer Science,Social Sciences |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4416183743 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Mehmet Arzu](https://scholariq.org/researchers/mehmet-arzu/)

## Paper primary topic

- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)

## Paper topics

- [Sentiment Analysis and Opinion Mining](https://scholariq.org/topics/sentiment-analysis-and-opinion-mining/)
- [Spam and Phishing Detection](https://scholariq.org/topics/spam-and-phishing-detection/)
- [Digital Marketing and Social Media](https://scholariq.org/topics/digital-marketing-and-social-media/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.