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This study aims to explore the influencing factors on college students’ behaviours of spreading Internet public opinion on emergencies in colleges and universities. This study provides a reference for these institutions to cope with and reduce the influence of Internet public opinion on emergencies and maintain their normal teaching order.

In this study, a research model by using motivation theory and design a questionnaire on the basis of relevant literature are constructed. This paper surveys college students and collects a total of 317 valid questionnaires. On the basis of the reliability and validity of the questionnaire, this study verifies the proposed model by using Smart PLS.

The results show that social motivation and information source preference have significant positive influences on college students’ willingness to spread Internet public opinion on emergencies in colleges and universities. Moreover, information source preference has a significant moderating effect on the relationship between social motivation and dissemination willingness. If college students’ information source preference is high, then the moderating effect is significant. The extent of college students’ interaction and involvement has a significantly positive influence on their trust in the dissemination platform for Internet public opinion on emergencies in colleges and universities. Egoism has a significantly positive influence on the social motivation of college students to spread Internet public opinion on emergencies in colleges and universities. Involvement degree has a significant moderating effect on the relationship between social motivation and trust. If college students’ involvement degree is low, then the moderating effect is significant. Thus, when the involvement of college students in Internet public opinion on emergencies in colleges and universities is low, the influence of social motivation on trust is great.

This study increases the influencing factors in the literature on Internet public opinion, enriches the research theory of Internet public opinion on emergencies in colleges and universities and expands the application scope of the theory of social motivation. The conclusion provides guidance for colleges and students to govern Internet public opinion on emergencies and improve the ability of these institutions in dealing with Internet public opinion on emergencies.

The sudden outbreak of COVID-19 has become a major public health emergency of global concern. Studying the Internet public opinion dissemination mechanism of public health emergencies is of great significance for creating a legalized network environment, and it is also helpful for managers to make scientific decisions when encountering Internet public opinion crisis.

Based on the analysis of the process of spreading the Internet public opinion in major epidemics, a dynamic model of the Internet public opinion spread system was constructed to study the interactive relationship among the public opinion events, network media, netizens and government and the spread of epidemic public opinion. The Shuanghuanglian event in COVID-19 in China was taken as a typical example to make simulation analysis.

Research results show three points: (1) the government credibility plays a decisive role in the spread of Internet public opinion; (2) it is the best time to intervene when Internet public opinion occurred at first time; (3) the management and control of social media are the key to public opinion governance. Besides, specific countermeasures are proposed to assist control of Internet public opinion dissemination.

The epidemic Internet public opinion risk evolution system is a complex nonlinear social system. The system dynamics model is used to carry out research to facilitate the analysis of the Internet public opinion propagation mechanism and explore the interrelationship of various factors.

This study aims to improve disaster management. Social media, particularly microblog, has become a new platform for public opinion dissemination. However, few studies have been conducted to explore the structure of public opinions, the approaches for facilitating the spread of public opinions and the results of public opinion dissemination in the context of mobile internet for the purpose of improving disaster management.

This paper chooses Ebola as the research topic and extracts 14,735 Ebola-related data items from Sina Microblogs to examine the information nodes of public opinion and the characteristics of propagation paths on mobile internet. Particularly, nodes of public opinion between mobile terminals and non-mobile terminals are compared.

The results of this paper reveal the characteristics of public opinion propagation on mobile internet and verify the effectiveness of public opinion propagation on mobile internet. This study shows that public opinions propagate quickly, widely and efficiently and further generate great impacts on mobile internet.

The methods used in this study can be useful for the government agencies and other relevant organizations to monitor public opinions, identify issues and problems proactively and develop strategies in a more efficient manner to improve disaster management.

The results of this paper are helpful for related departments to monitor public opinions and to further improve disaster management.

This paper explores the mechanism of public opinion dissemination on mobile internet and further investigates how to improve disaster management through a case study related to Ebola.

Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks.

This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals.

The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet.

The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.

This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”

The purpose of this paper is to evaluate and rank the influence of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence with TOPSIS.

This disaggregation method includes four main steps, determine the vector of weights for the factors by analytic hierarchy process, calculate the matrix of consistent effect measure, determine the weighted absolute degree of grey incidence with TOPSIS, rank and evaluate the events.

We get the ranking of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence with TOPSIS. The result can be used for evaluating and ranking the influence of internet public opinion in China. The positive weighted absolute degree of grey incidence, the negative weighted absolute degree of grey incidence and the weighted absolute degree of grey incidence with TOPSIS have the same ranking results. The same ranking results show that the method of weighted absolute degree of grey incidence with TOPSIS has good consistency.

The weighted absolute degree of grey incidence with TOPSIS can be easily used for other evaluation.

The weighted absolute degree of grey incidence with TOPSIS is proposed and first used for evaluating and ranking the influence of internet public opinion of China’s Government work.

The purpose of the study was to assess the representation of different world views with respect to climate change in public opinion on the internet.

The authors conducted this world views analysis by means of a content analysis of publicly expressed opinions in the form of online lay reader comments to articles on climate change, published on Dutch newspaper web sites between August 2002 and December 2009. The comments were assigned to the world views of two typologies commonly used in ex ante assessment of climate policies. The classification of an online reader comment was based on world view specific keywords and positions on climate change.

From a set of 2,148 comments to 168 articles found on the web sites of 19 newspapers, 314 comments could be assigned to a particular world view. For both typologies, the distribution of comments over the different world views was highly uneven, with world views characterized as “climate sceptic” scoring more than 90 per cent of the assigned comments. The strong dominance of these “climate sceptic” world views was independent of year, newspaper, and scope of the article.

These findings are in stark contrast with the outcomes of public opinion surveys indicating that only a minority of the population has a preference for a “climate sceptic” world view. The most plausible explanation for this difference is that the contributors of online reader comments are not representative for the Dutch population at large. However, as internet-based opinions have a proven potential to strongly influence the opinion of the general public and politicians on climate change, the authors advise analysts to pay due attention to “climate sceptic” world views in ex ante assessment of the societal support for climate policies.

For a world views analysis, the study is unique both in its focus on internet public opinion and the data source used.

In the new era of highly developed Internet information, the prediction of the development trend of network public opinion has a very important reference significance for monitoring and control of public opinion by relevant government departments.

Aiming at the complex and nonlinear characteristics of the network public opinion, considering the accuracy and stability of the applicable model, a network public opinion prediction model based on the bald eagle algorithm optimized radial basis function neural network (BES-RBF) is proposed. Empirical research is conducted with Baidu indexes such as “COVID-19”, “Winter Olympic Games”, “The 100th Anniversary of the Founding of the Party” and “Aerospace” as samples of network public opinion.

The experimental results show that the model proposed in this paper can better describe the development trend of different network public opinion information, has good stability in predictive performance and can provide a good decision-making reference for government public opinion control departments.

A method for optimizing the central value, weight, width and other parameters of the radial basis function neural network with the bald eagle algorithm is given, and it is applied to network public opinion trend prediction. The example verifies that the prediction algorithm has higher accuracy and better stability.

Internet-famous food (also known as “online celebrity” food) is very popular in the digital age. This study aims to investigate consumer attitudes and understand consumer behavior towards Internet-famous food.

The authors collected 136,835 online comments regarding “Internet-famous food” from Dianping platform between 2016 and 2019 using a web scraper. A sentiment lexicon for Internet-famous food was constructed, and sentiment analysis is further conducted to understand consumer attitudes. Additionally, the authors use topic analysis and time series analysis to study consumer behavior.

Sentiment analysis showed that the number of consumers' comments decreased over time with the attitudes being overall positive, and the Internet-famous food industry has a positive prospect; time series analysis showed that the consumption of Internet-famous food was not affected by the season; topic analysis showed that consumers' comments on Internet-famous food were rich with a large variety, covering food categories, brand, quality, service, environment and price.

To the authors’ knowledge, limited research has focused on public opinions regarding “Internet-famous food”. This is the first study on consumer behavior towards Internet-famous food. This article provides a unique insight into the purchasing behavior and attitude of Chinese Internet-famous food consumers through text mining.

Research on opinion polarization in the USA repeatedly finds more divergence among politically privileged groups: respondents who are college educated, politically interested, party identified or have a liberal/conservative orientation. The purpose of this paper is to examine whether their excluded counterparts can be polarized by exposure to political information on the internet.

Quantile regression and visual analysis of raw data from the online and face-to-face samples in the 2012 and 2016 American National Election Studies (n=9,563) assessed the impact of online political information on opinion polarization among ideological moderates, political Independents, respondents without a college degree, and those with low interest in politics.

Exposure to online political information during the survey was associated with significant polarizing shifts toward more consistent ideological positions in all four groups.

Engaging the middle is a social justice issue as much as a matter of political conflict, and evidence suggests that politically excluded groups use the internet to translate their own views into the language of policy opinions and popular (polarized) politics. Recommended policy interventions include information literacy programs. Further research should use experimental models and browser histories.

Current research on political polarization leaves open the question of whether larger portions of the electorate are available to join the fray. This study shows that excluded publics can be polarized via exposure to online information.

This paper aims to demonstrate how blog searching can be used as a retrospective source of public opinion.

In this paper a variety of blog searching techniques are described and illustrated with a case study of the Danish cartoons affair.

A time series analysis of related blog postings suggests that the Danish cartoons issue attracted little attention in the English‐speaking world for four months after the initial publication of the cartoons, exploding only after the simultaneous start of diplomatic sanctions and a commercial boycott.

Blogs only reveal the opinions of bloggers, and blog analysis is language‐specific. Sections of the world and the population of individual countries that do not have access to the internet will not be adequately represented in blogspace. Moreover, bloggers are self‐selected and probably not representative of internet users.

The existence of blog search engines now allows researchers to search blogspace for posts relating to any given debate, seeking either the opinions of blogging pundits or casual mentions in personal journals. It is possible to use blogs to examine topics before they first attract mass media attention, as well as to dissect ongoing discussions. This gives a retrospective source of public opinion that is unique to blog search engines.