数据与计算发展前沿2026，Vol.8Issue(1)：91-102,12.DOI:10.11871/jfdc.issn.2096-742X.2026.01.008
一种基于情感分析的网络舆论倾向性检测方法
Network Public Opinion Tendency Detection Method Based on Sentiment Analysis
摘要
Abstract
[Application Background]With the vigorous development of online social media,controver-sial online public opinions occur frequently,bringing numerous potential risks and challenges to society.As an effective approach for determining public opinion trends,sentiment analysis holds significant importance in the study of online public opinion.[Method]This paper pres-ents an opinion tendency detection method based on BERT.This method devises a deep learn-ing classifier for sentiment tendency analysis and,simultaneously,incorporates the contrastive learning strategy.[Conclusion]The proposed method deepens the model's representation of po-larized disputes,remarkably improves the performance of negative public opinion tendency de-tection,and enhances the ability to detect public opinion polarization.This research offers a practical technical solution for detecting online public opinion risks,facilitating the timely iden-tification and response to potential negative public opinions and polarized disputes,thus safe-guarding the health and stability of the online environment.关键词
情感分析/深度学习/对比学习/舆论分析/两极化争议Key words
sentiment analysis/deep learning/contrastive learning/public opinion analysis/polarized disputes引用本文复制引用
邓绎如,何洪波,王英,王闰强..一种基于情感分析的网络舆论倾向性检测方法[J].数据与计算发展前沿,2026,8(1):91-102,12.基金项目
中国科学院网络安全和信息化专项(CAS-WX2022GC-0304) （CAS-WX2022GC-0304）
