Public Opinion Management Research Articles

Napoléon et l’Empire de l’opinion : acteurs et enjeux du contrôle de l’opinion publique sous le Premier Empire

This article outlines the history of the administration in charge of the regulation and control of public opinion during the French Empire. The context of this regulation is delineated by examining how Napoleon intended, as early as the Consulate, to merge the Ancien Regime traditions with the new values of the Revolution. This project acknowledges innovative developments in public opinion management, in the shaping of political legitimacy after 1789. I will examine three unpublished manuscripts produced by this administration in order to illustrate the administrative and political implications of the imperial control of public opinion. In addition, I will analyze the historical issues at stake determined by different figures who played a role in this administration.

Feature Representation and Organization Method for Public Opinion Big Data Based on Association Analysis

In order to improve the data mining level of public opinion big data, by analysing the relationship among semantic web, ontology and RDF (Resource Description Framework), the structure and organization method of public opinion big data association data are separated. Based on the analysis of network public opinion big data organization technology, and then the RDF structure definition of network public opinion knowledge map is given, and the construction method of RDF association analysis map of network public opinion knowledge is realized. Experimental research shows that the proposed method can provide more accurate correlation analysis of public opinion big data, which can effectively realize the analysis and management of public opinion hot events, and provide decision support for the management of network public opinion.

Profiling the Users of High Influence on Social Media in the Context of Public Events

The highly influential users on social media platforms may lead the public opinion about public events and have positive or negative effects on the later evolution of events. Identifying highly influential users on social media is of great significance for the management of public opinion in the context of public events. In this study, the highly influential users of social media are divided into three types (i.e., topic initiator, opinion leader, and opinion reverser). A method of profiling highly influential users is proposed based on topic consistency and emotional support. The event of “Jiankui He Editing the Infants' Genes” was investigated. The three types of users were identified, and their opinion differences and dynamic evolution were revealed. The comprehensive profiles of highly influential users were constructed. The findings can help emergency management departments master the focus of attention and emotional attitudes of the key users and provide the method and data support for opinion management and decision-making of public events.

Dynamic assessment of Internet public opinions based on the probabilistic linguistic Bayesian network and Prospect theory

In the evolution of an emergency, Internet public opinions usually catalyze escalation and spread of the emergency, and even affect the evolution of public opinions. Therefore, how to effectively manage Internet public opinions has become urgent. As an essential part of the Internet public opinion management, assessing the heat degree of Internet public opinions is necessary. Being problem-oriented, this paper analyzes the development and evolution of Internet public opinions, and identifies the characteristics of the heat degree assessment of Internet public opinions. Taking into account the continuously changing exterior environment, the dynamic nature of Internet public opinions, and the inadequacy and uncertainty of decision-making information, assessing the heat degree of Internet public opinions is regarded as a dynamic multi-attribute decision making problem under the probabilistic linguistic environment. Thus, this paper aims to develop a dynamic decision-making framework to assess the heat degrees of Internet public opinions under the probabilistic linguistic environment. First, the probabilistic linguistic Bayesian network (PLBN) is constructed, in which the nodes denote attributes and related factors, and the hierarchical network structure shows the relationship among attributes. Then, the probability information obtained by PLBN in the form of PLTS is converted into attribute weight information. Moreover, this paper starts from the nature of PLTS, discusses PLTSs in terms of the probability distribution, and then gives the concept of the dominance degree of PLTS, based on which, a dynamic decision-making model based on the idea of prospect theory that considers DMs’ bounded rationality is developed. Finally, five emergency events happened in China are selected as a case to illustrate the proposed approach and some analyses and discussions have been carried out to verify the validity of our approach.

G-GERT network model of online public opinion reversal based on kernel and grey degree

PurposeIn recent years, online public opinion reversal incidents have been occurring frequently, which has increased the complexity of the evolution of online public opinion, and they have become a difficult issue for public opinion management and control. It is of great significance to explore the regularity of online public opinion reversal.Design/methodology/approachCombined with the grey characteristics of online public opinion information, a grey graphical evaluation review technique (G-GERT) network model is constructed based on kernel and grey degree, and the frequency, probability and time of online public opinion reversal nodes are calculated using C-marking method and Z-marking method.FindingsThroughout the online public opinion reversal events, there are all repeated outbreak nodes occurring, so the authors regard the repeated occurrence of outbreak nodes as reversal. According to the average frequency, probability and time of repeated outbreak nodes in the G-GERT network model, the authors predict the corresponding key information of reversal. It can simulate the evolution process of public opinion events accurately.Originality/valueThe G-GERT network model based on kernel and grey degree reveals the regulation of public opinion reversal, predicts the frequency, probability and time of reversal nodes, which are the most concerned and difficult issues for decision-makers. The model provides the decision basis and reference for government decision-making departments.

Thinking and Exploration Based on Wechat for Government Affairs in Governance of Public Opinions in the New Media Era

With the rapid development of China’s mobile Internet technology and the increasing number of smart phone users, we have embraced the era of new media. WeChat has been part and parcel of people in daily life for information transmission and communication. WeChat is capable of transforming general public topics into public events, which presents a new challenge to the government’s response to public opinion crisis. Therefore, how to build a governance mechanism for public opinion is a major test of China’s governing capacity and it is a realistic topic to improve the government’s credibility. Research on solution to the problem of government public opinion management in the WeChat based new media era has important practical significance for the government to do a good job in public opinion management in the new media era in an efficient manner.

Modelling the Latent Semantics of Diffusion Sources in Information Cascade Prediction.

Predicting the information spread tendency can help products recommendation and public opinion management. The existing information cascade prediction models are devoted to extract the chronological features from diffusion sequences but treat the diffusion sources as ordinary users. Diffusion source, the first user in the information cascade, can indicate the latent topic and diffusion pattern of an information item to mine user potential common interests, which facilitates information cascade prediction. In this paper, for modelling the abundant implicit semantics of diffusion sources in information cascade prediction, we propose a Diffusion Source latent Semantics-Fused cascade prediction framework, named DSSF. Specifically, we firstly apply diffusion sources embedding to model the special role of the source users. To learn the latent interaction between users and diffusion sources, we proposed a co-attention-based fusion gate which fuses the diffusion sources' latent semantics with user embedding. To address the challenge that the distribution of diffusion sources is long-tailed, we develop an adversarial training framework to transfer the semantics knowledge from head to tail sources. Finally, we conduct experiments on real-world datasets, and the results show that modelling the diffusion sources can significantly improve the prediction performance. Besides, this improvement is limited for the cascades from tail sources, and the adversarial framework can help.

Research on the evolution and prediction of Internet public opinion of major pandemics—Taking the COVID-19 pandemic as an example

To clarify the evolutionary law of major epidemics online public opinion is a prerequisite for targeted public opinion management. This article takes the Novel Coronavirus Pneumonias as an example and proposes a method to predict the hot spots of public opinion in epidemic. We firstly used the python web crawler technology to capture 58916 online public opinion data on the Novel Coronavirus Pneumonias of the Forum on ‘Making the Country Prosperous’ of People’s Daily Online from January to March 2020, and then used the jieba thesaurus for word segmentation and keyword extraction, and performed word frequency statistics to show the hot content of the new crown epidemic network public opinion, then through the keyword association rule mining to find out the hot topics, finally through the information entropy to evaluate the hot topics, and discover potential hot topics in the future.

Hotspot Discovery in the Field of Emergency Management

[Purpose/Significance] Real time analysis and mining of hot spots and the research trends of domestic scholars in the field of emergency management are the basic work to promote the theory and application of emergency management. [Methods/Process] Using the Bibliometrics method and CiteSpace visual analysis tool, the key words of 1619 domestic emergency management documents from 2013 to 2019 were mapped and clustered to identify the hot spots of emergency management research; Through the co-occurrence matrix and similarity matrix of high-frequency keywords, the research trend of emergency management is further explored; [Results/Conclusions] The research results show that the research focus of domestic emergency management mainly focuses on 21 topics, such as public opinion management and control, emergency coordination, emergency network and system optimization, emergency resource capacity reserve, disaster risk assessment etc.

Strategic Optimization of Public Opinion Management in Universities under Change of Network Public Opinion Ecosystem

The current breakthroughs in Internet big data and AI technologies have accelerated the fission-like dissemination of public opinion on the Internet, providing both opportunities and challenges for university governance. Universities should adapt to the new situation of the ecological change of public opinion with subject, object, carrier and environment as the elements, and optimize the public opinion management mechanism of universities from five levels: building a management system of network public opinion, strengthening the guidance mode of public opinion, promoting the operation of campus new media matrix, paying attention to the education of students’ network media literacy, and focusing on the construction of open internal and external communication platform, purifying the network space, maintaining the image of universities, and creating a Double First-class construction of universities and necessary ecology.

Human mobility in interest space and interactive random walk

Compared with the well-studied topic of human mobility in real geographic space, only a few studies focus on human mobility in virtual space, such as interests, knowledge, ideas, and so on. However, it relates to the issues like public opinion management, knowledge diffusion, and innovation. In this paper, we assume that the interests of a group of online users can span an Euclidean space which is called interest space, and the transfers of user interests can be modelled as Lévy Flight in the interest space. Considering the interaction between users, we assume that the random walkers are not independent but interacting with each other indirectly via the digital resources in the interest space. The proposed model in this paper successfully reproduced a set of scaling laws for describing the growth of attention flow networks of online communities, and obtaining similar ranges of users’ scaling exponents with empirical data. Further, we inferred parameters for describing the individual behaviours of the users according to the scaling laws of empirical attention flow network. Our model can not only provide theoretical understanding of human online behaviours but also has broad potential applications such as dissemination and public opinion management, online recommendation, etc.

Public opinion information dissemination in mobile social networks – taking Sina Weibo as an example

PurposeSocial 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.Design/methodology/approachThis 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.FindingsThe 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.Social implicationsThe methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.Originality/valueThis 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.”

ПОВІДОМЛЕННЯ ПРЕССЛУЖБ ОРГАНІВ ПУБЛІЧНОЇ ВЛАДИ РЕГІОНАЛЬНОГО РІВНЯ: СТРУКТУРА ТА СТИЛІСТИКА

<p>The article discusses the structural and stylistic aspects of the posts from press services of the<br />Dnipropetrovsk and Odessa regional state administrations, which are available on their websites. The<br />relevance of this study is caused by the transformation of the system of mass communication of public<br />authorities with citizens, in particular, the expansion of the sphere of direct contacts of public authorities<br />with their target audiences without the mediation of the media and the need to form a complete<br />cycle of media production on the basis of press services. This requires an appropriate level of organization<br />of communication of public authorities with the public and the qualification of staff.<br />The purpose of the article is to identify the structural and stylistic features of the posts from press<br />services of regional public authorities on their websites.<br />Studies performed using methods: comparative analysis, content analysis, analysis and synthesis.<br />It has been demonstrated that news posts from press services on official web-sites of regional-level<br />public authorities have styling features of both PR-products and journalistic works. It is suggested that<br />this is due to the desire to implement in one information flow its own information function and the function<br />of public opinion management.<br />Comparison of posts from the press services regional state administrations revealed different approaches<br />to the structure and stylistics of these texts. The materials of the press service of the Dnepropetrovsk<br />Regional State Administration are structured according to a single model and stylistically<br />close to publications in Internet editions, and Odessa – have structural differences, but stylistically<br />more to press releases. In studied reports revealed a number of common stylistic defects, indicating a<br />need for further work to improve the quality of media products.<br />Key words: press service, web site, structure of media reports, style of media reports, public authorities.</p>

Evaluation of Network Public Opinion on the Doctor-Patient Relationship Based on Evolutionary Game Theory

Effective management of public opinion on the doctor-patient relationship network is an important element of maintaining social harmony and stability. In this paper, a new tripartite evolutionary game is proposed, the purpose of which is to examine the behavioral strategies of doctors, governments and netizens in the evolution of public opinion on the doctor-patient relationship network. Secondly, we further propose evolutionary replication dynamics equations in order to study the evolutionary stable strategies of participants. Select Shaanxi “Yulin puerpera fall from a building” as a case study, the applicability of the method was demonstrated and the main factors affecting the behavior of participants were found. Finally, we put forward suggestions on the management and control of public opinion on the doctor-patient relationship network from the four perspectives of doctors, government, media, and netizens. Research shows that the development of public opinion on the doctor-patient relationship network is the result of the joint action of multiple participants.

Evolutionary Game Model of Public Opinion Information Propagation in Online Social Networks

The rapid development of communication technology has greatly changed the way of information propagation. While making use of positive public opinion information in online social networks (OSN) to create value, it is necessary to manage and control the propagation of public opinion. Considering the existence of both positive and negative public opinion, we proposed a tripartite evolutionary game model through identifying the relevant stakeholders involved in the public opinion spreading process, discussed the equilibrium conditions of stakeholders’ behavior strategies emphatically and carried out simulation experiments. Then, based on the experimental results, the management strategy and the key intervention points of public opinion spreading were proposed. The result shows that the key to management and control public opinion is realizing the interest balance of all stakeholders. That is, the government should increase the benefits of netizens and media spreading (reporting) positive public opinion, and at the same time strengthen the punishment of them spreading (reporting) negative public opinion. This paper further expands the research of public opinion propagation in OSN, and provides theoretical support and decision-making basis for the management and control of public opinion.

Three-hop velocity attenuation propagation model for influence maximization in social networks

In the study of influence maximization in social networks, the speed of information dissemination decreases with increasing time and distance. The investigation of the characteristics of information dissemination is of great significance to the management and control of public opinion. A three-hop velocity decay propagation model is proposed to determine the propagation speed in information dissemination and the time and distance attenuation factors of information dissemination were modeled. We simulated the three-hop information propagation and developed an influence maximization algorithm based on the rate attenuation propagation model (IMMRA). Experiments using two example data sets showed that the proposed algorithm had higher accuracy and time efficiency than a greedy algorithm.

Restoring incomplete PUMLPRs for evaluating the management way of online public opinion

In the age of big data explosion, the management of online public opinion has encountered great challenges. Which way can effectively manage online public opinion has become a decision-making question for us to think about. Probabilistic uncertain multiplicative linguistic preference relations (PUMLPRs) are a remarkable instrument to solve uncertain evaluation problems. This paper uses the PUMLPRs to assess the management ways of the online public opinion. Owing to the intricacy of decision-making domain, the PUMLPRs are not always complete. We get the complete PUMLPRs in two steps: the repair for uncertain multiplicative linguistic variables and the repair for probability. Moreover, the consistency of the complete PUMLPRs is researched. Then the final priorities are obtained by the proposed possibility degree formula. After that, the numerical example that helps assess the valid way to manage online public opinion is performed to check the feasibility of the proposed decision-making procedure.

Effect of the Quality of Microblog Information Content on Internet Public Opinion Dissemination

In the era of mobile internet, microblog has become the main source of information for people, and its information quality is crucial. From the perspective of information content quality, this paper constructs a quality index system of microblog information content, uses correlation analysis and empirical analysis to verify the impact of relevant indicators on the dissemination of public opinion, and concludes that the quality of microblog information content has a positive impact on the transmission of microblog. Finally, the key quality factors affecting the dissemination of public opinion are obtained, which can provide reference for the management of network public opinion.

Research on Management Model of Network Public Opinion Based on Big Data Technology

The national big data strategy not only provides policy support for economic development transformation and technical guidance for social management reform, but also brings opportunities and challenges to the management of network public opinion for the government. In order to systematically guide the practice work of the government to manage network public opinion, this work first analyzed the challenges faced by network public opinion management under the background of big data, and then proposed the mechanism and technology of network public opinion management based on big data.

Research on the Construction of Early Warning Index System of Network Public Opinion Emergency Based on Computer Simulation

Under the current social background of our country, the dissemination environment, dissemination background, audience characteristics, media environment and event types of network public opinion are constantly developing and changing, and the influencing factors will also have new changes. The early warning index system of network public opinion emergencies is an important part of the crisis management of network public opinion. The analysis of network public opinion is based on the complete and accurate grasp of network public opinion. The early warning of network public opinion emergencies is based on the full exploitation and utilization of network public opinion data. Through the analysis and judgment of public opinion, the early warning mechanism of network public opinion emergencies can be improved. Computer simulation is a fast and economical important research tool, and the effectiveness and accuracy of computer simulation depends on the performance of computer simulation software tools. Using computer simulation and simulation of the process of user concept in event propagation, dynamic evolution simulation of events is analyzed according to the results of user concept, and hot events are identified.