Research on Unsupervised Method for Changing Trend Evaluation of Internet Public Opinion Events

被引：0
|
作者：
Qin T. [1 ]
Wang X. [1 ]
Shen Z. [1 ]
Chen Z. [2 ]
Ding J. [2 ]
机构：
[1] MOE Key Lab for Intelligent and Network Security, Xi'an Jiaotong University, Xi'an
[2] Science and Technology on Communication Security Lab, 30th Research Institute of China Electronics Technology Group Corporation, Chengdu
来源：
Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University | 2020年 / 54卷 / 11期
关键词：
Bessel curve; Limited resources; Public opinion management; Unsupervised learning;
D O I：
10.7652/xjtuxb202011014
中图分类号：
学科分类号：
摘要：
Aiming at the abruptness posed by public opinion emergencies, limited labeled data and management resources, we proposed an unsupervised algorithm for evaluating the importance of public opinion changing trend and controlling the important public opinion events within limited time and reducing their harmful influence to the society. Firstly, the importance of changing trend evaluation problem is transformed into a multi-index ranking based on the management experience. Secondly, to solve the problems posed by limited labeled data, we use the principal curve algorithm to formulate the problem of changing trend evaluation, and use the third-order Bessel curve to obtain the final ranking results. The designed model can fully capture the structural and value characteristics of the original data. Finally, we employ the typical public data set and the self-built public opinion event data set to verify the proposed method. The experimental results verify that the developed method has high efficiency in public opinion event changing trend ranking without prior knowledge, and provides a decision support for public opinion event management with limited resources. © 2020, China Food Publishing Company. All right reserved.
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页码：113 / 120
页数：7
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