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<p>Due to the abundance of unstructured material on the internet, opinion mining has become a popular method for academics, corporations, and researchers to extract data for the purpose of collecting, analysing, and aggregating human sentiments. Several enterprises in the market have benefited greatly from the aspect-level textual analysis of popular sentiment. Recently, higher levels linguistic characteristics have been acquired by methods that use deep learning avoiding the necessity for feature development. Consequently, the primary emphasis of this study is a thorough assessment on a primary subsection of aspect-based sentiment analysis (ABSA) methods: aspect extraction. A thorough examination of the newest and most advanced aspect extraction techniques demonstrates the noteworthy progress in the ABSA industry.</p>

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Recent approaches for aspect based sentiment analysis: a review

  • 期刊论文

  • 发表日期：

    2026年1月13日

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  • Ganpat Singh Chauhan,
  • Ravi Nahta,
  • Abhishek Upadhyay,
  • Yogesh Kumar Meena,
  • Dinesh Gopalani,
  • Akash Saxena

摘要

Due to the abundance of unstructured material on the internet, opinion mining has become a popular method for academics, corporations, and researchers to extract data for the purpose of collecting, analysing, and aggregating human sentiments. Several enterprises in the market have benefited greatly from the aspect-level textual analysis of popular sentiment. Recently, higher levels linguistic characteristics have been acquired by methods that use deep learning avoiding the necessity for feature development. Consequently, the primary emphasis of this study is a thorough assessment on a primary subsection of aspect-based sentiment analysis (ABSA) methods: aspect extraction. A thorough examination of the newest and most advanced aspect extraction techniques demonstrates the noteworthy progress in the ABSA industry.