Public Opinion Guidance of the Network System in Colleges and Universities

2020 ◽  
pp. 491-496
Author(s):  
Baozhi Wang
Keyword(s):  
Public Opinion ◽  
Colleges And Universities ◽  
Network System

scholarly journals Analysis of the Countermeasures of Dealing with the Network Public Opinions on Emergencies of Colleges in Gansu Province

2020 ◽  
Vol 4 (9) ◽  
Author(s):  
Jianwen Duo ◽  
Jin Wang ◽  
Zhengyan Zhan ◽  
Pinghui Yang
Keyword(s):  
Public Opinion ◽  
Colleges And Universities ◽  
Gansu Province ◽  
The Internet ◽  
Public Attention ◽  
Timely Manner ◽  
Local Society ◽  
Short Period ◽  
Safety And Stability ◽  
Network Public Opinion

The popularity of the Internet and the rise of self-media have built a diversified, convenient and instant platform for colleges and universities to do a good job in education, teaching, propaganda and ideology, but at the same time it also brings challenges and problems of college network security and campus stability. Most emergencies in colleges and universities are caused by trivial incidents and are largely unpredictable. If they are put online through online channels, they will attract the attention of the majority of netizens in a short period of time and attract online public attention. Once it is not handled in a timely manner, it will affect the normal education and teaching of colleges and universities and the safety and stability of campuses, and it is likely to form major public opinion on a larger scale, affecting the harmony and stability of the local society. This article adopts the characteristics of the network public opinion of colleges and universities in Gansu Province. It analyzes the current situation and focuses on the countermeasures to deal with network public opinion caused by emergencies in colleges and universities, hoping to provide a reference for further promoting the level and effectiveness of network public opinion in response to emergencies in Gansu Province.

scholarly journals Sentimental Knowledge Graph Analysis of the COVID-19 Pandemic Based on the Official Account of Chinese Universities

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2921
Author(s):  
Xiaolin Li ◽  
Zhiyi Li ◽  
Yahe Tian
Keyword(s):  
Public Opinion ◽  
New Media ◽  
Sentiment Analysis ◽  
Topic Model ◽  
Colleges And Universities ◽  
Mobile Internet ◽  
Knowledge Graph ◽  
Analysis Model ◽  
Governance System ◽  
Network Public Opinion

With the advent of the new media mobile Internet era, the network public opinion in colleges and universities, as an extension of social network public opinion, is also facing a crisis in the prevention, control, and governance system. In this paper, the Fiddler was used to collect the comments and other relevant data of the COVID-19 topic articles on the WeChat Official Accounts of China’s top ten universities in 2020. The BILSTM_LSTM sentiment analysis model was used to analyze the sentiment tendency of the comments, and the LDA topic model was used to mine the topics of the comments with different emotional attributes at different stages of COVID-19. Based on sentiment analysis and text mining, entities and relationships in the theme graph of public opinion events in colleges and universities were identified, and the Neo4j graph database was established to construct the sentimental knowledge graph of the pandemic theme of university public accounts. People’s attitudes in university public opinion are easily influenced by a variety of factors, and the degree of emotional disposition changes over time, with the stage the pandemic is in, and with different commentators; official account opinion topics change with the development of the time stage of the pandemic, and students’ positive and negative comment topics show a diverse trend. By incorporating topic mining into the sentimental knowledge graph, the graph can realize functions such as the emotion retrieval of comments on university public numbers, a source search of security threats in university social networks, and monitoring of comments on public opinion under the theme of the pandemic, which provides new ideas for further exploring the research and governance system of university network public opinion and is conducive to preventing and resolving campus public opinion crises.

scholarly journals Analysis of Public Opinion in Colleges and Universities Based on Wireless Web Crawler Technology in the Context of Artificial Intelligence

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
WenNing Wu ◽  
ZhengHong Deng
Keyword(s):  
Artificial Intelligence ◽  
Public Opinion ◽  
Colleges And Universities ◽  
Web Crawler ◽  
The Public ◽  
User Influence ◽  
Proposed Model ◽  
Wide Range ◽  
Different Dimensions ◽  
The Web

Wi-Fi-enabled information terminals have become enormously faster and more powerful because of this technology’s rapid advancement. As a result of this, the field of artificial intelligence (AI) was born. Artificial intelligence (AI) has been used in a wide range of societal contexts. It has had a significant impact on the realm of education. Using big data to support multistage views of every subject of opinion helps to recognize the unique characteristics of each aspect and improves social network governance’s suitability. As public opinion in colleges and universities becomes an increasingly important vehicle for expressing public opinion, this paper aims to explore the concepts of public opinion based on the web crawler and CNN (Convolutional Neural Network) model. Web crawler methodology is utilised to gather the data given by students of college and universities and mention them in different dimensions. This CNN has robust data analysis capability; this proposed model uses the CNN to analyse the public opinion. Preprocessing of data is done using the oversampling method to maximize the effect of classification. Through the association of descriptions, comprehensive utilization of image information like user influence, stances of comments, topics, time of comments, etc., to suggest guidance phenomenon for various schemes, helps to enhance the effectiveness and targeted social governance of networks. The overall experimentation was carried out in python here in which the suggested methodology was predicting the positive and negative opinion of the students over the web crawler technology with a low rate of error when compared to other existing methodology.

Simulation and Algorithm of Network Public Opinion Based on a New Wavelet Threshold

2014 ◽  
Vol 543-547 ◽  
pp. 3650-3654
Author(s):  
Jun Li Yu
Keyword(s):  
Public Opinion ◽  
Colleges And Universities ◽  
Threshold Function ◽  
Ideological And Political Work ◽  
Political Work ◽  
Better Regulation ◽  
Simulation Results ◽  
Threshold Network ◽  
Network Public Opinion

According to the existing deficiency of the process of network public opinion for the ideological and political work in colleges and universities, we put forward a new threshold network public opinion algorithm. Compared with the network public opinion algorithm which has the traditional soft and hard threshold and the existing threshold, the new algorithm has overcome the error about the estimation between network public opinion and the real public opinion, and has better regulation and continuity. Simulation results show that it can improve the quality of network public opinion by using the new threshold function, and reduce the intensity of interference on students.

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