现代信息科技2024，Vol.8Issue(10)：123-127,5.DOI:10.19850/j.cnki.2096-4706.2024.10.025
基于BERT的用户评论情感分析
Sentiment Analysis of User Comments Based on BERT
摘要
Abstract
Sentiment Analysis(SA)is a very important sub-task of Natural Language Processing(NLP)in the Internet era,which can help users to analyze comments and public opinion.However,most existing studies focus on improving the overall performance of sentiment analysis tasks,and there are few categorical studies targeting different text features.Classification research can help researchers find the shortcomings of current analysis methods in specific scenarios,and can also guide users to choose more appropriate analysis methods when facing different scenarios.Based on the BERT model,SentiHood is classified according to text length and number of evaluation targets,and different analysis methods are used to conduct group experiments.The experimental results show that each method performs better in short text analysis than in long text analysis,and the performance of single objective analysis is better than that of multi-objective analysis.Under different text features,there are different analysis methods that demonstrate optimal performance.关键词
情感分析/文本特征/BERTKey words
SA/text feature/BERT分类
信息技术与安全科学引用本文复制引用
漆阳帆..基于BERT的用户评论情感分析[J].现代信息科技,2024,8(10):123-127,5.
