方面级情感分析综述

doi:10.11896/jsjkx.220400077

Abstract

Abstract: Sentiment analysis is one of the important branches of natural language processing.With the development of the times,in order to extract more sentiment information from text,aspect-level sentiment analysis is paying more and more attention in sentiment analysis.Firstly,this paper introduces the background knowledge and related concepts of aspect-level sentiment analysis,and explains it from the perspective of two subtasks of aspect extraction and aspect sentiment classification.In terms of aspect extraction,related methods based on similarity algorithms,topic models and sequence labeling are introduced.In terms of aspect sentiment classification,related methods based on sentiment lexicon and rules,machine learning and deep learning are introduced,and the Chinese and English data sets and sentiment lexicon commonly used in aspect-level sentiment analysis are sorted out.Finally,making a summary and outlook for the current challenges and future development directions of aspect-level sentiment analysis.

Key words: Sentiment analysis, Aspect extraction, Aspect sentiment classification, Sentiment lexicon, Deep learning

CLC Number:

TP391.9

LI Yang, WANG Shi, ZHU Junwu, LIANG Mingxuan, GAO Xiang, JIAO Zhixiang. Summarization of Aspect-level Sentiment Analysis[J].Computer Science, 2023, 50(6A): 220400077-7.

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