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

Ha Le, Bao Tran, Phuong Le, Tan Nguyen, Dac Nguyen +2 more
1/2/2024
cs.CL

No official code found. Best implementation: lthha/comparative-opinion-mining (3 stars, last commit 2024-01-03).

Abstract

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.

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Code Implementations(1)

lthha/comparative-opinion-miningCommunity100%

Finetune multiple pre-trained Transformer-based models to solve challenge on Comparative Opinion Mining from Vietnamese Product Reviews in VLSP2023 shared task.

30PythonSep 29, 20232 years ago

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Cite this paper

@article{le2024unveiling,
  title  = {Unveiling Comparative Sentiments in Vietnamese Product Reviews: A Sequential Classification Framework},
  author = {Ha Le and Bao Tran and Phuong Le and Tan Nguyen and Dac Nguyen and Ngoan Pham and Dang Huynh},
  year   = {2024},
  eprint = {2401.01108},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.01108v1}
}

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