Predicting Model in Network Impact: a Monitoring and Warning System for Public Opinion in Universities under Big Data Framework
Liu Xiangdong1, Cao Yuting2, Li Limei3
1.Department of Statistics, School of Economics, Jinan University, Guangzhou, Guangdong, 510632; 2.School of Foreign Languages, Jinan University, Guangzhou, Guangdong, 510632; 3.Office of the President, Shenzhen University, Shenzhen, Guangdong, 518060
Abstract：The Internet has great impact on the dissemination of ideas, and in particular public opinion, among college students. Under these new circumstances, it is of great significance to build up and gradually improve a monitoring and warning system for public opinion in universities, which will enable us to know how the students think, and address relevant issues in order to help them to establish the correct "three-values". This paper proposes a monitoring system for college student online public opinion, a predicting model of user influence based on the continuous time Markov process, through which we will find the most influential users (key figures) the social network of college students. With an automatic text classification method based on machine learning, the key figures are mainly classified into three categories: positive key figures, neutral key figures, and negative key figures. Finally, the paper proposes some measures in accordance with different types of key figures to promote the development of social networking service for college students.
柳向东, 曹雨婷, 李利梅. 网络影响力预知模型：一种大数据下高校舆情监测与预警机制[J]. 《深圳大学学报》（人文社科版）, 2015, 32(4): 156-160.
Liu Xiangdong,Cao Yuting, Li Limei. Predicting Model in Network Impact: a Monitoring and Warning System for Public Opinion in Universities under Big Data Framework. , 2015, 32(4): 156-160.
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2015, Vol. 32 
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