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Natural language processing (NLP) has several key applications, including sentiment analysis (SA). SA can be described as a procedure that identifies the polarity of a sentence as well as its goal through analysis. SA is now the most active NLP research area. Aspect-based sentiment analysis, which is a subset of SA, is the process of examining a sentence’s structure and determining its polarity. This field has been grown because now people feel free to share their thoughts, opinions, expressions. Internet, social media are now the massive resource of opinion assuming. In this paper, we have used SemEval 2014 task 4 dataset to focus on Aspect-based Sentiment Analysis (ABSA) problem. We have focused on previous work Based on Aspect-based Sentiment Analysis and Some work of Sentiment Analysis based on conversational data. We have used GPT2 for this task.

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Dependency of Sentiment on Its Aspect Using Large Language Model

  • 会议论文

  • 发表日期：

    2026年

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  • Rupsa Sarkar,
  • Jaydev Mishra

摘要

Natural language processing (NLP) has several key applications, including sentiment analysis (SA). SA can be described as a procedure that identifies the polarity of a sentence as well as its goal through analysis. SA is now the most active NLP research area. Aspect-based sentiment analysis, which is a subset of SA, is the process of examining a sentence’s structure and determining its polarity. This field has been grown because now people feel free to share their thoughts, opinions, expressions. Internet, social media are now the massive resource of opinion assuming. In this paper, we have used SemEval 2014 task 4 dataset to focus on Aspect-based Sentiment Analysis (ABSA) problem. We have focused on previous work Based on Aspect-based Sentiment Analysis and Some work of Sentiment Analysis based on conversational data. We have used GPT2 for this task.