A statistical model of the impact of online rumors on the information quantity of online public opinion

Lan, Yubin; Lian, Zhixuan; Zeng, Runxi; Zhu, Di; Xia, Yixue; Liu, Mo; Zhang, Peng

doi:10.1016/j.physa.2019.123623

Cited by 23 publications

(16 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, Pankowska et al [13] built a national medical policy system based on this model and proposed that the integration and evaluation of several system variables can effectively promote the efficiency of related policy decisions. Some researchers selected carbon dioxide emissions as the simulation result parameter to select and optimize environmental policies [14]; Boeschoten et al [15] simulated five subsystems of economy, market, policy, environment, and application industries, targeting the coal-bed methane industry. e policy puts forward a number of recommendations; Bertoni et al [16] simulated the impact of several variables on the national food supply and demand situation and provided certain theoretical support for the national oil and grain policy analysis.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Forecast and Simulation of the Public Opinion on the Public Policy Based on the Markov Model

2021

Complexity

View full text Add to dashboard Cite

Public policy and public opinion directly affect the image of the government, but due to the lack of appropriate monitoring and early warning tools, the government’s handling of credit changes is seriously lagging behind. In response to this problem, this paper integrates the internet, public information, market credit information, and other data, uses hidden Markov models and natural language processing technology, and establishes a modern government public policy and public opinion monitoring and early warning model to evaluate government credit in real time; the government can formulate relevant policies based on the evaluation results to improve the government’s governance capabilities. Empirical analysis shows that, based on the dynamic scoring framework and Markov model, the government credit monitoring and early warning models established, respectively, have 90% of the reference value, and the analysis results have the same reference. This method can effectively predict the trend of hot online public opinion. The subsequent establishment of an online public opinion early warning system and an online public opinion guidance mechanism provided theoretical support.

show abstract

Section: Related Workmentioning

confidence: 99%

[Retracted] Forecast and Simulation of the Public Opinion on the Public Policy Based on the Markov Model

2021

Complexity

View full text Add to dashboard Cite

show abstract

“…At first, the accuracy in term of CNN‐based politics public opinion analysis is simulated, and the experiment results under different dissemination models are shown in Table 1. Among them, BenC1 and BenC2 are two abbreviations and selected as benchmarks from references 7,8 respectively.…”

Section: Methodsmentioning

confidence: 99%

CNN‐based politics public opinion analysis of undergraduates: A case study with CDN deployment

Xie

2021

Internet Technology Letters

View full text Add to dashboard Cite

In the era of social media, the political speech of undergraduates blots out the sky and covers up the earth, which perhaps generates the negative effect. To enhance the management ability of government departments, it is considerably necessary to pay more attention to the public opinion. However, the current researches on the public opinion mainly focus on mathematical modeling or data mining irrespective of public opinion analysis. Consider that Convolutional Neural Network (CNN) has the strong data analysis ability, this paper uses CNN to realize the special application, that is, politics public opinion analysis of undergraduates, which has two functions. On one hand, greatly help the government departments eliminate the crisis timely; On the other hand, correctly guide the political education of undergraduates. Besides, this paper also presents a case study based on Content Delivery Network (CDN) deployment, in which a monitor system of public opinion analysis is implemented to analyze the undergraduates' political speech. Finally, with three public opinion dissemination modes consideration, the experiments are made. The results show that CNN has better training ability and the whole deployment is more significant compared to the state‐of‐the‐art schemes.

show abstract

“…As a kind of false information, rumors attract wide attention and high public opinion due to their wide spread. Lan et al and Liu indicated that online rumors prompt the public to generate more online public-opinion topics about the event, the amount of online public opinion would continue to increase, and the upper limit of this increase was difficult to predict [41,42]. On the basis of the above analysis, the third proposition is defined: message attributes influence the rebound of public opinion of public emergencies.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?

Gao

Zhang

Liu

2021

IJERPH

View full text Add to dashboard Cite

The rebound of online public opinion is an important driving force in inducing a secondary crisis in the case of public emergencies. Effective risk-information communication is an important means to manage online public opinion regarding emergencies. This paper employs fuzzy-set qualitative comparative analysis to discover which conditions are combined and may result in the rebound of online public opinion. Five conditions were selected: the type of public emergency, messengers, message attributes, audience, and information feedback. The study used a sample of 25 major public emergencies that occurred between 2015 and 2020 in China. The type of public emergency, audience, and information feedback emerged as critical influencing factors. Message attributes promote the rebound of online public opinion regarding public health emergencies, while messengers play a traction role in the rebound of online public opinion on other types of public emergencies. This study extends risk-information communication theory from the perspective of the type of emergency, explores the causes of rebounded online public opinion regarding public emergencies, and provides policies and suggestions for risk-information communication and online public-opinion governance during emergencies.

show abstract

A statistical model of the impact of online rumors on the information quantity of online public opinion

Cited by 23 publications

References 25 publications

[Retracted] Forecast and Simulation of the Public Opinion on the Public Policy Based on the Markov Model

[Retracted] Forecast and Simulation of the Public Opinion on the Public Policy Based on the Markov Model

CNN‐based politics public opinion analysis of undergraduates: A case study with CDN deployment

How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?

Contact Info

Product

Resources

About