摘要
[目的/意义]旨在构建一个网络舆情系统,及时准确地挖掘海量网络数据,分析社会热点事件的网络舆情。[方法/过程]结合深度学习技术,构建了一个基于内容与结构的舆情分析模型,其中利用Bi LSTM-CNN深度模型对舆情内容进行情感分析,利用社会网络分析法对舆情网络进行结构分析。[结果/结论]实证分析表明了该模型在公共事件舆情分析上的有效性和优越性。从结构和内容两方面分析,能为公共事件网络舆情分析提供新思路。
[Purpose/significance]The paper is to construct a network public opinion system to promptly and accurately mine massive network data and analyze network public opinion of social hotspots.[Method/process]The paper combines deep learning technology to construct a public opinion analysis model based on content and structure.The BiLSTM-CNN depth model is used to analyze the sentiment and the social network analysis method is used to analyze the structure.[Result/conclusion]Empirical analysis shows the effectiveness and superiority of the model in public opinion analysis of public events.Analyzing from two aspects of structure and content can provide new ideas for network public opinion analysis of public events.
作者
朱乐
李秋萍
朱燚丹
Zhu Le;Li Qiuping;Zhu Yidan(School of Mathematics and Physics China University of Geosciences(Wuhan),Wuhan Hubei 430074)
出处
《情报探索》
2020年第6期40-47,共8页
Information Research
关键词
深度学习
网络舆情
情感分析
社会网络分析法
deep learning
network public opinion
sentiment analysis
social network analysis
