University Public Opinion Research Articles

An Innovative Scheme for the Governance of Religious Online Public Opinion in Universities: A Design Based on the 4R Crisis Management Theory

The emergency management of religious online public opinion is an important part of the management work in universities, and the modernization of college governance in the new era. Based on the review of relevant theories and concepts of religious online public opinion in universities, this article analyzes the problems existing in the governance of religious online public opinion in universities from the perspective of 4R crisis management theory through literature analysis and questionnaire survey. Coping strategies are proposed for the governance of religious online public opinion in universities, and a “reduction-preparation-response-recovery” governance model of religious online public opinion is constructed, providing reference for the effective response and governance of religious online public opinion in universities.

The Generation and Avoidance Path of Emotional Turn in College Online Public Opinion in the Post Truth Era

On November 16, 2016, the Oxford Dictionary first defined the term "post truth" as the "annual vocabulary" of 2016, which refers to emotions and personal beliefs being more influential than objective facts in influencing public opinion. Since then, the "post truth" has also been increasingly concerned and discussed by the academic community. This article takes the "post truth era" as the theoretical background to explore the reasons and manifestations of the emotional shift in online public opinion in universities, and proposes corresponding response strategies.

Strategies for Monitoring and Managing Online Public Opinion in Universities Under the Background of Big Data

<p>In response to the issue of some keywords not being logged in or having inaccurate semantics in current public opinion monitoring, this article uses an improved word segmentation method to extract semantic features. In response to the current issue of unable to control the emotional direction of public opinion comments in public opinion analysis, an emotion analysis model Bi_GRU is proposed for sentiment analysis. Finally, using students’ commonly used Weibo as a verification scenario, sensitive information such as “food safety” and “campus bullying” is screened to control the emotional direction of college students. The final proof is that the method proposed in this article can effectively supervise public opinion in a centralized environment and provide effective means for student management. </p> <p> </p>

Research on the communication strategy of university public opinion event report from the perspective of frame theory: Shandong University Buddy Program Incident as an example

Research on the communication strategy of university public opinion event report from the perspective of frame theory: Shandong University Buddy Program Incident as an example

Research on endogenous internet public opinion dissemination in Chinese universities based on SNIDR model

During an emergency, the negative Internet public opinion in colleges and universities, especially the negative endogenous public opinion, will have a serious impact on the reputation of colleges and universities. It is of great significance to find out the negative influencing factors of endogenous public opinion and explore the mechanism of public opinion dissemination for resolving the crisis of public opinion in universities. The existing research does not distinguish the endogenous Internet public opinion in colleges and universities from the general Internet public opinion in colleges and universities, and the SIR model adopted fails to fully reflect the difference between students and other dissemination subjects of endogenous public opinion in campus. In addition, various research methods and models currently used focus on the static expression of dissemination results, and the explanation of results is insufficient. The reason is that they do not well express the dynamic interaction mechanism between influencing factors and the dynamic conversion rate between roles. In this study, based on the improved infectious disease model and system dynamics theory, AnyLogic software is used to simulate the improved SNIDR model of infectious disease, to analyze the sensitivity of school supervision, school intervention, school response time and information transparency and to study the dynamic conversion rate between different roles. The SNIDR model effectively simulates the process of endogenous public opinion dissemination in colleges and universities after emergencies. The results show that, what has the greatest impact on the dissemination of public opinion is the school’s supervision and intervention efforts, which can suppress the dissemination from the source. Information transparency is an auxiliary variable and cannot function independently. During the dissemination period, the timelier the school responds, the faster the spreaders will drop to zero, and the better it will be to control the secondary dissemination of public opinion.

Research on the Guiding Path of Online Public Opinion in Universities from the Perspective of Public Management

Research on the Guiding Path of Online Public Opinion in Universities from the Perspective of Public Management

Research on College Network Early Warning Based on LSTM

With the development of information technology and the continuous optimization of China’s education system, college students have gradually become the main group in the Internet, and college network public opinion events have received increasing attention. By analyzing the constituent elements of university network public opinion, building an early warning indicator system from three dimensions: subject, carrier, and object, and combining life cycle theory, dynamic comprehensive evaluation method, and short-term memory network, constructing a university network public opinion model. Through empirical analysis of 20 university network public opinion events, the experimental results show that the proposed public opinion model has certain feasibility. Corresponding response strategies have also been proposed for different levels of crisis warning, providing a decision-making basis for relevant departments to guide and manage online public opinion in universities.

Research on University Network Public Opinion Monitoring and Early Warning System Based on Big Data

Undergraduate self-consciousness is still in the formative stage and is highly susceptible to external environment. Schools must adapt to the new forms and requirements, improve their ability to search, analyze, and prevent online public opinion through big data technologies; we should make early discovery, early action, and early resolution, so as not to give time and space for public opinion crisis fermentation and consolidate the dominant position of the mainstream ideology. This paper focuses on the university network public opinion monitoring and early warning system based on big data and analyzes the university public opinion from the perspective of the specificity, sensitivity, identification, early warning and prevention ability of the system to deal with public opinion, and effectively solves the network public opinion crisis. Combined with the current actual situation and specific needs, this paper explores the intervention measures and guidance strategies for the network public opinion of college emergencies, so as to lay a solid foundation for the healthy, stable, and sustainable development of colleges and universities.

A Data-Driven Approach for University Public Opinion Analysis and Its Applications

In the era of mobile Internet, college students increasingly tend to express their opinions and views through online social media; furthermore, social media influence the value judgments of college students. Therefore, it is vital to understand and analyze university online public opinion over time. In this paper, we propose a data-driven architecture for analysis of university online public opinion. Weibo, WeChat, Douyin, Zhihu and Toutiao apps are selected as sources for collection of public opinion data. Crawler technology is utilized to automatically obtain user data about target topics to form a database. To avoid the drawbacks of traditional methods, such as sentiment lexicon and machine learning, which rely on a priori knowledge and complex handcrafted features, the Word2Vec tool is used to perform word embedding, the LSTM-CFR model is proposed to realize Chinese word segmentation and a convolutional neural network (CNN) is built to automatically extract implicit features in word vectors, ultimately establishing the nonlinear relationships between implicit features and the sentiment tendency of university public opinion. The experimental results show that the proposed model is more accurate than SVM, RF, NBC and GMM methods, providing valuable information with respect to public opinion management.

Intelligent Analysis and Positioning of Political Public Opinion in Universities

With the rapid development of Internet technology, the network has become an indispensable way of life for undergraduates. The correct guidance of public opinion has also become an important thing in the ideological work of universities. Undergraduates are in an important period of formation and development of thoughts that they are easily to be incited by cyber-rumors. Therefore, it is particularly important to obtain the data of political public opinion in universities and position the hot topics for early detection of political public opinion tendency, which can also avoid the outbreak of major security incidents. With such consideration, this paper obtains multi-source political public opinion data from BBS, Tieba and Weibo of SUN YAT-SEN UNIVERSITY (SYSU) through crawler. We study a text feature extraction method based on Word2Vec & LDA (Latent Dirichlet Allocation), which improves the high-dimensional sparsity in traditional Vector Space Model (VSM) text representation. Meanwhile, based on the classical Single-pass clustering algorithm, this paper studies the Single-pass & HAC clustering algorithm. In addition, a measurement method of hot topic is defined to calculate the heat value of political public opinion. Dictionary and rule based method is used to improve the accuracy of sentiment tendency analysis. The experimental results demonstrate that the effect of topic detection and positioning based on LDA & Word2Vec and Single-pass & HAC algorithm is better than other methods.

Application Analysis of Emotional Learning Model Based on Improved Text in Campus Review and Student Public Opinion Management

In an era of rapid mobile Internet development, students are increasingly expressing their views on specific events through campus comments. In the Web 2.0 era, the concept of public media participation is widely used by students, and it is important to effectively analyze online campus public opinion comments and present the findings in a rationalized form for the management of campus public opinion. In the new era of education governance modernization, the level of public opinion management in universities has become a key indicator to improve the standard of education management in higher education institutions; therefore, this paper focuses on proposing an innovative deep learning-based research method for topic management of university public opinion. Firstly, through the improved LDA module with sentiment discrimination learning capability, the sentiment of the main arguments in the campus commentary is extracted, and then the statistical sentiment intensity of the in-depth learning module is used to analyze the sentiment intensity of the thematic arguments of different events in time series, so as to achieve the long-term tracking of the trend of the sentiment intensity of the whole event.

Research on the construction of quantitative index of microblog group polarization in university public opinion events

“We Media” have enabled netizens to express their opinions in a freer and more convenient way. Netizens’ speech tends to be deviated after group discussion, resulting in online public opinion group polarization and irrational behaviours. Here, a quantitative index of Microblog public opinion group polarization has been established based on the sentiment analysis of the comment text, the popularity of comments and the interaction of users' @. Besides, the effectiveness of such index has been verified by simulation experiment, aiming to provide decision-making thinking and method guidance for Microblog public opinion group polarization determination.

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

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.

Evolution and Hot Spot Analysis of University Public Opinion Analysis from the Perspective of Knowledge Map

In this paper, CiteSpace software is used to make statistics and Analysis on the literature related to public opinion research in Colleges and universities in China in recent years collected by CNKI, and visually display and analyze the literature data through the way of knowledge map, and also reveal the research status, research hotspots and trends in this field in a visual way. In recent years, the research in the field of public opinion in Colleges and universities has achieved sustained development, but there is a lack of high impact authors of core categories, and researchers have not formed a certain degree of concern; with the development of the network, the current research direction in this field mainly focuses on campus public opinion, network public opinion, emergency public opinion, new media public opinion, but the research force has not formed a scale We can rely on the new media and network technology to further expand the research of public opinion in Colleges and universities from the perspective of crisis management and ideological and political construction.

The Exploring on the Supervision of University Public Opinion in the Background of Big Data

College public opinion are a reflection of the ideological status of college students and the degree of campus stability. The high frequency and suddenness of public opinion events and the speed and virtuality of the information age have brought new opportunities and challenges to public opinion supervision and public opinion intervention. In the new era, the supervision of network public opinion in colleges and universities should conform to the characteristics of the era of big data, use advanced information technology to improve the efficiency of supervision, and strive to achieve the goal of scientific decision-making management. Based on the major colleges and universities, this paper aims to explore the improvement program of college public opinion supervision under the background of big data. It uses literature review method, research method and experimental method to analyse. This paper analyzed the current situation of network public opinion supervision in colleges, summed up the problems existing in the network of colleges, and constructed a network public opinion supervision platform for colleges under the background of big data.

Comparative Study of University Public Opinion Communication Network Based on SNA

Comparative Study of University Public Opinion Communication Network Based on SNA

Comparative Study of University Public Opinion Communication Network Based on SNA

Comparative Study of University Public Opinion Communication Network Based on SNA

Support for Offering Sexual Health Services Through School-Based Health Clinics.

Numerous studies document support for sexuality education in the schools. However, there is a dearth of research assessing support for sexual health services offered through school-based health clinics (SBHCs). The purpose of this study was to assess voter support for offering 3 sexual health services (STI/HIV testing, STI/HIV treatment, condom distribution) through SBHCs. The survey was developed after review of existing surveys on support for sexuality education and sexual health services. The university's Public Opinion Research Laboratory used random-digit-dialing to administer the survey to participants (N = 311) including residential and cell phone numbers. Most participants were supportive of offering sexual health services at both middle schools (MS) and high schools (HS): testing for STIs/HIV (61% MS, 76% HS), treatment for STIs/HIV (60% MS, 75% HS), and provision of condoms (44% MS, 63% HS). Analyses showed significant differences in support for sexual health services by a few demographic variables, opinions about sexuality education, and the percentage of students perceived to have had sexual intercourse. Results document support for offering sexual health services through SBHCs. These findings may benefit other communities looking to implement similar clinics. Such services have great potential for positively impacting the sexual health of youth.

Predictors of Support of Legislation Banning Juvenile Executions in Oklahoma: An Examination by Race and Sex

The Supreme Court has recently decided to re‐examine the constitutionality of executing individuals under the age of 18 at the time of the offense. The Supreme Court’s reliance on public opinion as evidenced through opinion polls and changing laws in the 2002 Atkins decision has suggested that public opinion may play a role in the Court’s decision regarding juvenile executions. There is considerable evidence that the majority of Americans favor a ban on juvenile executions. In the current study, we use Oklahoma data collected in 2003 by the Oklahoma University Public Opinion Learning Laboratory to examine more closely the factors that predict a support of a ban on juvenile executions. Interestingly, only one fourth of Oklahomans oppose such a ban. Earlier research suggested that religious fundamentalism is linked to support of juvenile executions, but we did not find this, suggesting that public opinion may be shifting. We then analyzed the data separately by race and then by sex. Our findings suggest that there may be differences between groups in the predictors of support for a ban on juvenile executions, at least in Oklahoma, indicating the need for further research.