# Unveiling Comparative Sentiments in Vietnamese Product Reviews: A Sequential Classification Framework

arXiv: https://arxiv.org/abs/2401.01108 · HTML: https://mlsanity.com/paper/2401.01108/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 9 references that are in the map.
- First posted on arXiv 2 Jan 2024.

## Builds on (most cited first, 3 of 3)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [PhoBERT: Pre-trained language models for Vietnamese](https://mlsanity.com/paper/2003.00744/) (2020)
- [Pre-training Language Models for Comparative Reasoning](https://mlsanity.com/paper/2305.14457/) (2023)

## Built on by (most cited first, 1 of 1)

- [Comparative Opinion Mining in Product Reviews: Multi-perspective Prompt-based Learning](https://mlsanity.com/paper/2412.08508/) (2024)

## Abstract (arXiv)

Comparative opinion mining is a specialized field of sentiment analysis that aims to identify and extract sentiments expressed comparatively. To address this task, we propose an approach that consists of solving three sequential sub-tasks: (i) identifying comparative sentence, i.e., if a sentence has a comparative meaning, (ii) extracting comparative elements, i.e., what are comparison subjects, objects, aspects, predicates, and (iii) classifying comparison types which contribute to a deeper comprehension of user sentiments in Vietnamese product reviews. Our method is ranked fifth at the Vietnamese Language and Speech Processing (VLSP) 2023 challenge on Comparative Opinion Mining (ComOM) from Vietnamese Product Reviews.