scholarly journals Combining Public Opinion Dissemination with Polarization Process Considering Individual Heterogeneity

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 176 ◽  
Author(s):  
Tinggui Chen ◽  
Jingtao Rong ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li
Keyword(s):  
Public Opinion ◽  
Formation Mechanism ◽  
Individual Heterogeneity ◽  
State Transitions ◽  
False Information ◽  
Seir Model ◽  
Relationship Strength ◽  
Transmission Parameters ◽  
Proposed Model ◽  
Wide Dissemination

The wide dissemination of false information and the frequent occurrence of extreme speeches on online social platforms have become increasingly prominent, which impact on the harmony and stability of society. In order to solve the problems in the dissemination and polarization of public opinion over online social platforms, it is necessary to conduct in-depth research on the formation mechanism of the dissemination and polarization of public opinion. This article appends individual communicating willingness and forgetting effects to the Susceptible-Exposed-Infected-Recovered (SEIR) model to describe individual state transitions; secondly, it introduces three heterogeneous factors describing the characteristics of individual differences in the Jager-Amblard (J-A) model, namely: Individual conformity, individual conservative degree, and inter-individual relationship strength in order to reflect the different roles of individual heterogeneity in the opinions interaction; thirdly, it integrates the improved SEIR model and J-A model to construct the SEIR-JA model to study the formation mechanism of public opinion dissemination and polarization. Transmission parameters and polarization parameters are simulated and analyzed. Finally, a public opinion event from the pricing of China’s self-developed COVID-19 vaccine are used, and related Weibo comment data about this event are also collected so as to verify the rationality and effectiveness of the proposed model.

scholarly journals Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity

Mathematics ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 917 ◽  
Author(s):  
Chen ◽  
Li ◽  
Yang ◽  
Cong ◽  
Li
Keyword(s):  
Public Opinion ◽  
Individual Heterogeneity ◽  
Initial Time ◽  
Polarization Phenomenon ◽  
Simulation Experiments ◽  
Polarization Model ◽  
The Public ◽  
Proposed Model ◽  
Initial Attitude ◽  
Opposite Attitude

Nowadays, hot issues are likely become bipolar or multipolar after heated discussion on the Internet. This article is focused on the study of the polarization phenomenon and establishes a public opinion polarization model with the considerations of individual heterogeneity and dynamic conformity. At first, this article introduces the dynamic changing function of an individual’s conformity tendency to other’s attitudes in the interaction process. It further defines the influential weight between different interactive individuals, and expands the interactive individual from complete homogeneity to initial attitude heterogeneity, and finally, conformity heterogeneity. Then, through simulation experiments, we find that the degree of changing in individual attitude is limited. That is, it is difficult for the individuals who have one directional attitude at the initial time to change into another opposite attitude through interaction. In addition, individuals with low conformity within a certain threshold are more likely to form polarization. Finally, the rationality and effectiveness of the proposed model are verified by the typical case “Mimeng Event”.

scholarly journals A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wilfredo Angulo ◽  
José M. Ramírez ◽  
Dany De Cecchis ◽  
Juan Primera ◽  
Henry Pacheco ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Risk Perceptions ◽  
Transmission Rate ◽  
Early Stage ◽  
Individual Risk ◽  
Seir Model ◽  
Proposed Model ◽  
Probable Site ◽  
Adjusted Model ◽  
The Impact

AbstractCOVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.

scholarly journals An SEIR Model for Assessment of Current COVID-19 Pandemic Situation in the UK

2020 ◽  
Author(s):  
Peiliang Sun ◽  
Kang Li
Keyword(s):  
Seasonal Influenza ◽  
Time Lag ◽  
Seir Model ◽  
Infected People ◽  
Proposed Model ◽  
Lag Effect ◽  
Novel Coronavirus ◽  
The Uk ◽  
Specific Symptoms ◽  
Limited Testing

AbstractThe ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long incubation period, high fatality ratio and non-specific symptoms, making this novel coronavirus far different from common seasonal influenza. In this note, we present a modified SEIR model which takes into account the time lag effect and probability distribution of model states. Based on the proposed model, it is estimated that the actual total number of infected people by 1 April in the UK might have already exceeded 610,000. Average fatality rates under different assumptions at the beginning of April 2020 are also estimated. Our model also reveals that the R0 value is between 7.5–9 which is much larger than most of the previously reported values. The proposed model has a potential to be used for assessing future epidemic situations under different intervention strategies.

Aristocrats, Gypsies, and Cowboys All: Film Stereotypes and Hungarian National Identity in the 1930s

2002 ◽  
Vol 30 (3) ◽  
pp. 383-401 ◽  
Author(s):  
David S. Frey
Keyword(s):  
National Identity ◽  
Public Opinion ◽  
False Information ◽  
Or Groups ◽  
The World ◽  
Walter Lippmann

Among social psychologists, there has long been a debate over the concept of the stereotype. Are stereotypes meant mainly for consumption by an in-group or are they designed by and for curious outsiders? Are they primarily individual or collective? Are they benign generalizations and categories that make it easier for individuals or groups to perceive and organize the world around them? Or are they insipid and unsustainable generalizations, based on false information, exaggeration, unfairly rigid conceptual categories, or even the observer's laziness? Do they beget understanding or prejudice? These questions, many of which were first raised by Walter Lippmann when he published Public Opinion in 1922, still polarize the psychological profession today. They also continue to confound politicians who wish to construct coherent, distinct, and vibrant identities for their nations.

The cooperative and competitive mechanisms of a leader’s opinion transmission

2020 ◽  
Vol 31 (09) ◽  
pp. 2050127
Author(s):  
Adil Amirjanov
Keyword(s):  
Public Opinion ◽  
Numerical Experiments ◽  
Continuous Model ◽  
Opinion Formation ◽  
Agent Based ◽  
The Public ◽  
Proposed Model ◽  
Cooperative Process ◽  
Competitive Mechanisms ◽  
The Individual

The paper modeled a leader’s opinion transmission in a population. The proposed model develops the cooperation agent-based continuous model in which the cooperation of individuals is based on the similarity of evolved “tags” which are relative to evolved tag-difference tolerances. In proposed model, an individual’s opinion and the individual’s tolerance are specified as variables in the model. During communication with each other and with a leader, the resources of individuals are incremented, if they are tolerable to the opinions of their opponents. An opinion formation in population is established by a cooperative process — changing individual’s opinion, if the individual is tolerable to the opinions of opponents, and by a competitive process — copying opinions and tolerances of successful individuals who have higher resource. Numerical experiments have proven that the public opinion reached a consensus followed the leader’s opinion.

scholarly journals Control of COVID-19 outbreak using an extended SEIR model

2021 ◽  
pp. 1-26
Author(s):  
Sean T. McQuade ◽  
Ryan Weightman ◽  
Nathaniel J. Merrill ◽  
Aayush Yadav ◽  
Emmanuel Trélat ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Optimal Strategies ◽  
Economic Cost ◽  
Contact Tracing ◽  
Economic Activities ◽  
Seir Model ◽  
Proposed Model ◽  
High Death ◽  
Containment Measures ◽  
The Cost

The outbreak of COVID-19 resulted in high death tolls all over the world. The aim of this paper is to show how a simple SEIR model was used to make quick predictions for New Jersey in early March 2020 and call for action based on data from China and Italy. A more refined model, which accounts for social distancing, testing, contact tracing and quarantining, is then proposed to identify containment measures to minimize the economic cost of the pandemic. The latter is obtained taking into account all the involved costs including reduced economic activities due to lockdown and quarantining as well as the cost for hospitalization and deaths. The proposed model allows one to find optimal strategies as combinations of implementing various non-pharmaceutical interventions and study different scenarios and likely initial conditions.

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.

scholarly journals An SEIR Model with Contact Tracing and Age-Structured Social Mixing for COVID-19 outbreak

2020 ◽  
Author(s):  
Ali Teimouri
Keyword(s):  
Reproduction Number ◽  
Contact Tracing ◽  
Seir Model ◽  
Expectation Value ◽  
Proposed Model ◽  
Social Mixing ◽  
The World ◽  
Age Structured ◽  
And Control ◽  
Explicit Relation

AbstractIn December 2019 a severe acute respiratory syndrome now known as SARS-CoV-2 began to surge in Wuhan, China. The virus soon spread throughout the world to become a pandemic. Since the outbreak various measures were put in place to contain and control the spread, these interventions were mostly based on compartmental models in epidemiology with the main goal of controlling and monitoring the rate of the basic and effective reproduction number. In this paper, we propose an SEIR model where we incorporate contact tracing and age-structured social mixing. We show the explicit relation between contact tracing and social mixing and other relevant parameters of the proposed model. We derive a formula for the effective reproduction number which is expressed in terms of reported cases, tracing quantities and social mixing. We use this formula to determine the expectation value of the effective reproduction number in London, UK.

An Improved Model of the Internet Public Opinion Spreading on Mass Emergencies

2013 ◽  
Vol 433-435 ◽  
pp. 1760-1764 ◽  
Author(s):  
Li Ma ◽  
Zhong Tian Jia ◽  
Hai Yan Sun ◽  
Chuan Yu
Keyword(s):  
Public Opinion ◽  
The Internet ◽  
Public Events ◽  
Effect Model ◽  
Proposed Model ◽  
The Social ◽  
Improved Model ◽  
Two Stages ◽  
Short Time ◽  
The Relationship

In the WEB2.0 environment, the report of public events will appear on the Internet as soon as they occur and attract a large number of peoples attention in a very short time. It is believed that the Internet public opinion represents the social public opinion. Hence, it is very valuable to study the relationship between the Internet public opinion and mass emergencies. In this paper, we proposed an improved effect model of the Internet public opinion spreading on mass emergencies. Different from the original model, we use variables as the parameters of the equation instead of constants and the whole mass emergency is divided into five stages. In the first two stages, the new participants proportion u(t) and the new leavers proportion v(t) holds the inequality u(t)≥v(t), and in the other stages, they hold u(t)≤v(t). Simulations show that the design of our proposed model can well fit the mass emergency development process.

scholarly journals Emotional characteristics and time series analysis of Internet public opinion participants based on emotional feature words

2020 ◽  
Vol 17 (1) ◽  
pp. 172988142090421 ◽  
Author(s):  
Fengzhen Jia ◽  
Chun-Chun Chen
Keyword(s):  
Time Series ◽  
Public Opinion ◽  
Rapid Development ◽  
Practical Application ◽  
Analysis Model ◽  
Evolution Analysis ◽  
Proposed Model ◽  
Tendency Analysis ◽  
Emotional Lexicon ◽  
Network Public Opinion

In recent years, with the rapid development and wide application of the Internet, it has become the main place for the generation and dissemination of public opinion. To grasp the information of network public opinion in a timely and comprehensive way can not only effectively prevent sudden network malignant events but also provide a reference for the scientific and democratic decision-making of government departments. Therefore, in view of the practical application needs, this article studies the emotional characteristics and the evolution of public opinion over time based on the emotional feature words of network public opinion participants. Firstly, the positive and negative emotional lexicon of HowNet emotional dictionary is used, and the commonly used emotional lexicon and expression symbols are added to the lexicon. At the same time, the polarity annotation method of Chinese emotional lexicon ontology is used to construct the emotional lexicon of this article. Secondly, considering other emotional polarity characteristics in the dictionary, an emotional tendency analysis model is proposed. In this article, emotional analysis is applied to the evolution analysis of network public opinion, and the change of network public opinion characteristics with time series is obtained. The simulation results show that the emotional dictionary constructed in this article and the proposed model of emotional orientation analysis can effectively analyze the emotional characteristics of network public opinion participants and apply emotional analysis to the evolution analysis of network public opinion, which can get the change of emotional characteristics of public opinion participants with time series.

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