Abstract
Network public opinion refers to the common opinion with tendency and influence formed by the public on certain social events through the Internet. Due to the complexity of interest relations, network public opinion is likely to cause difficulties for individuals, enterprises or governments. In order to control the public's emotional tendency to social events, this study designed an OCC sentiment rule system to label the network public opinion case base. The text representation method is Word2Vec in deep learning, and the convolution neural network is used to construct the sentiment tendency analysis model under the network public opinion. Taking the case of Dujia Banna humiliation incident, Xiangshui explosion incident and baixiangguo girl's murder as the research cases, the accuracy of the model to identify the above three events was 85.87%, 73.65% and 85.87% respectively under the optimal parameters setting. The experimental results show that compared with the manual annotation method, the proposed method can improve the accuracy of emotion recognition by 3.00% ~ 8.00%. This shows that the network public opinion sentiment orientation recognition model constructed in this study has a high recognition accuracy, and can be used to assist relevant departments to detect network public opinion.
Highlights
The dissemination and governance of network public opinion is an important part of government work, and the analysis of network public opinion sentiment tendency is the basic work to eliminate the network environment
The emotional orientation recognition model constructed in this study tends to provide a reference for relevant departments to monitor the network environment and control the direction of public opinion; it is more inclined to understand the negative comments of netizens on social events or social phenomena
The two-dimensional matrix generated by the Word2Vec model is the input of the convolution layer, the dimension of 7 × 5 vector matrix is reduced to 6 × 1 matrix, and the weight parameters are reduced, which reduces the operation difficulty and operation time of the convolution neural network
Summary
The dissemination and governance of network public opinion is an important part of government work, and the analysis of network public opinion sentiment tendency is the basic work to eliminate the network environment. Scholars have made a detailed analysis on the generation mechanism, evolution mechanism, impact on social economy, and guidance mechanism of network public opinion. Wu et al used the social network analysis (SNA) framework to analyze the generation mechanism and evolution process of network public opinion [1]. Based on the authenticity of network information dissemination, Hong’s team realized the simulation of the propagation process of food safety network public opinion events [6]. The research on the evolution mechanism of Internet public opinion and the analysis of emotional tendency about social events such as food, environment, and international disputes have been relatively perfect, but there are few studies on the universal model of emotional orientation analysis of network public opinion. This study relies on the standard emotional rule system to construct the identification model of netizens' emotional orientation to realize a comprehensive and efficient understanding of the emotion contained in the information text
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