Unveiling Comparative Sentiments in Vietnamese Product Reviews: A
  Sequential Classification Framework
Ha Le Bao Tran Phuong Le Tan Nguyen Dac Nguyen Ngoan Pham Dang Huynh
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.