Public Opinion Evolution Law and Sentiment Analysis of Campus Online Public Opinion Events

被引:1
作者
Xu, Zhengzhi [1 ]
Ye, Zi [2 ]
Ye, Haiyang [3 ]
Zhu, Lijia [4 ]
Lu, Ke [5 ]
Quan, Hong [5 ]
Wang, Jun [5 ]
Gu, Shanchuan [3 ]
Zhang, Shangfeng [6 ]
Zhang, Guodao [3 ]
机构
[1] Zhejiang Univ Water Resources & Elect Power, Modern Educ Technol Ctr, 508 2nd St, Hangzhou 310018, Zhejiang, Peoples R China
[2] Zhejiang Inst Econ & Trade, 280 Xuelin St, Hangzhou 310018, Zhejiang, Peoples R China
[3] Hangzhou Dianzi Univ, Dept Digital Media Technol, 1158 2nd St,Baiyang St, Hangzhou 310018, Zhejiang, Peoples R China
[4] Zhejiang Yuying Coll Vocat Technol, 16 4th St, Hangzhou 310018, Zhejiang, Peoples R China
[5] Zhejiang Univ Water Resources & Elect Power, 508 2nd St, Hangzhou 310018, Zhejiang, Peoples R China
[6] Zhejiang Gongshang Univ, Sch Stat & Math, 18 Xuezheng St,Xiasha Educ Pk, Hangzhou 310018, Zhejiang, Peoples R China
关键词
information systems; information retrieval; retrieval tasks and goals; sentiment analysis; public opinion analysis of campus; TWITTER;
D O I
10.20965/jaciii.2024.p0990
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the context of the new era, teachers and students in colleges and universities, as well as the general public, rely more on the Internet and social media to obtain news, express their opinions, and share information, and the dissemination of public opinion events in colleges and universities is not only related to the physical and mental health of teachers and students but also to the reform and development of colleges and universities. In this study, we took campus public opinion events as the main research object in which we selected three recent campus public opinion events to be analyzed. The public opinion data used in the research was collected from Weibo social media platforms. Firstly, we analyzed the dissemination cycle and regional dissemination patterns of a college food safety public opinion hot event through the popularity and regional distribution of public opinion data, thus revealing its formation and evolution patterns. Secondly, the LDA topic mining method is used to mine the themes of the three hot public opinion events, and then analyze the hot factors of the dissemination of each public opinion event from the massive public opinion data. This is crucial for the management department to grasp the dynamics of public opinion. Then, we used the SKEP sentiment classification method to analyze the emotional factors of the public opinion data of the three events to obtain the overall public opinion sentiment situation of the events. Finally, based on the characteristics of time, region, and gender, the evolution and diffusion rules of public topics and emotional distribution under different types of events are analyzed. The precision of the analyses associated with this paper may be limited to the effects of current mainstream as well as state-of-the-art analytical models. The analysis methods and conclusions in this paper provide a scientific theoretical basis and improvement measures for campus public opinion management, which helps to enhance the level of campus public opinion management and safeguard campus stability and public order.
引用
收藏
页码:990 / 1004
页数:15
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