Aspect-based Sentiment Analysis based on Feature Extraction and Attention

Bo He; Ruoyu Zhao; Lei Wang; Yongfen Yang

doi:10.54097/da7qvd31

Authors

Bo He
Ruoyu Zhao
Lei Wang
Yongfen Yang

DOI:

https://doi.org/10.54097/da7qvd31

Keywords:

Aspect-based Sentiment Analysis; Natural Language Processing; Sentiment Dictionary; Machine Learning; Deep Learning.

Abstract

Aspect-based Sentiment Analysis (ABSA) is a fine-grained sentiment analysis task whose goal is to analyze the sentiment polarity of specific aspects of a text. Currently, Aspect-based Sentiment Analysis is widely used in opinion analysis and content recommendation. In this paper, we provide an overview of Aspect-based Sentiment Analysis methods such as Sentiment Dictionary, Machine Learning, and Deep Learning, introduce their latest research results, and analyze the advantages and disadvantages of using different methods. The current status of research on Aspect-based Sentiment Analysis at home and abroad is analyzed in depth by combing this class of methods, and the future development and trends of textual Aspect-based Sentiment Analysis are proposed.

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