arXiv:2412.05591

BERTCaps: BERT Capsule for Persian Multi-Domain Sentiment Analysis

Mohammadali Memari, Soghra Mikaeyl Nejad, Amir Parsa Rabiei, Mehrshad Eisaei, Saba Hesaraki

제출 2024-12-07

원문 초록

Multidomain sentiment analysis involves estimating the polarity of an unstructured text by exploiting domain specific information. One of the main issues common to the approaches discussed in the literature is their poor applicability to domains that differ from those used to construct opinion models.This paper aims to present a new method for Persian multidomain SA analysis using deep learning approaches. The proposed BERTCapsules approach consists of a combination of BERT and Capsule models. In this approach, BERT was used for Instance representation, and Capsule Structure was used to learn the extracted graphs. Digikala dataset, including ten domains with both positive and negative polarity, was used to evaluate this approach. The evaluation of the BERTCaps model achieved an accuracy of 0.9712 in sentiment classification binary classification and 0.8509 in domain classification .

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논문 ID: publication/3527808공통 태그 Classification, Sentiment Analysis, Sentiment Classification

Twitter Sentiment Analysis

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