Tracing Public Opinion Propagation and Emotional Evolution Based on Public Emergencies in Social Networks

被引:35
|
作者
Wei-dong, H. [1 ]
Qian, W. [1 ]
Jie, C. [2 ]
机构
[1] Nanjing Univ Posts & Telecommun, Nanjing, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
opinion mining; the public opinion propagation; semantic classes; machine learning; STRUCTURAL BREAKS; VOLATILITY; BEHAVIOR; LEADERS; MODEL; OIL;
D O I
10.15837/ijccc.2018.1.3176
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Social network has become the main communication platform for public emergencies, and it has also made the public opinion influence spread more widely. How to effectively obtain public opinions from it to guide the healthy development of the society is an important issue that the government and other functional departments are concerned about. However, the interaction and evolution mechanism between the subject and the environment in the public opinion propagation is complicated, and the public and media attention and reaction to the incident are closely linked with the progress of the incident disposal. And public mining corpus has some shortcomings in the distribution of emotional classification. Only the timely update of artificial rules and emotional dictionary resources, it can handle new text data well. In fact, from the perspective of public opinion propagation, this paper built the network matrix between Internet users through the forwarding relationship, and used the social network analysis method and the emotion mining analysis technology to study the interaction and evolution mechanism between the subject and the environment in the public opinion propagation, and it studied the role of users in the emotional propagation of social networks. This paper proposed a sentiment analysis method on the micro-blog platform, which expanded the emotional dictionary and took sentence and emoticon and sentence patterns into account, which improved the accuracy of positive and negative classifications and emotional polarity analysis of the micro-blog.
引用
收藏
页码:129 / 142
页数:14
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