Public Opinion Propagation Model on Social Networks

2014 ◽  
Author(s):  
Jinlou Zhao ◽  
Junhui Cheng ◽  
Hongyu Gao
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Propagation Model

scholarly journals DR-SCIR Public Opinion Propagation Model with Direct Immunity and Social Reinforcement Effect

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 584 ◽  
Author(s):  
Weidong Li ◽  
Tianyi Guo ◽  
Yunming Wang ◽  
Bo Chen
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Propagation Model ◽  
Social Reinforcement ◽  
Reinforcement Effect ◽  
Factor B ◽  
Effect Factor ◽  
The Public ◽  
Simulation Results ◽  
First Time

The DR-SCIR network public opinion propagation model was employed to study the characters of S-state users stopping transmitting information for the first time and secondary transmission of immune users. The model takes into account symmetry and complexity such as direct immunization and social reinforcement effect, proposes the probability of direct immunity Psr and the probability of transform from the immune state to the hesitant state Prc, and divides public opinion information into positive public opinion and negative public opinion based on whether the public opinion information is confirmed. Simulation results show that, when direct immunity Psr = 0.5, the density of I-state nodes in the model decreased by 54.12% at the peak index; when the positive social reinforcement effect factor b = 10, the density of I-state nodes in the model increased by 16.67% at the peak index; and when the negative social reinforcement effect factor b = -10, the density of I-state nodes in the model decreased by 55.36% at the peak index. It shows that increasing the positive social reinforcement effect factor b can promote the spread of positive public opinion, reducing the negative social reinforcement effect factor b can control the spread of negative public opinion, and direct immunization can effectively suppress the spread of public opinion. This model can help us better analyze the rules of public opinion on social networks, so as to maintain a healthy and harmonious network and social environment.

Cross-network propagation model of public opinion information and its control in coupled double-layer online social networks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yun Li ◽  
Jiakun Wang
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Double Layer ◽  
Online Social Networks ◽  
Early Stage ◽  
Intervention Strategy ◽  
Propagation Model ◽  
Content Type ◽  
Propagation Law ◽  
Network Propagation

PurposeIn modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).Design/methodology/approachFirst, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.FindingsThe results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.Practical implicationsThis study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.Originality/valueThis research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.

Fake News im Wahlkampf

2021 ◽  
Author(s):  
Jessica Flint
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Fundamental Rights ◽  
Election Campaigns ◽  
Fake News ◽  
Forming Process ◽  
Private Companies ◽  
The Future

The urgency of regulating fake news on social networks regarding election campaigns is more evident than ever. This poses considerable difficulties for legislative practice. It is important to consider the fundamental rights of the parties involved without the state's influence on the formation of public opinion becoming too great. The current options of reacting to fake news do not suffice to ensure a free opinion-forming process. This publication makes an innovative proposal as to how social networks – especially Facebook – can be regulated in the future in such a way that the discourse is strengthened and the alarming influence of private companies on the formation of opinion is limited.

Grundrechtliche Einordnung sozialer Netzwerke vor dem Hintergrund des Netzwerkdurchsetzungsgesetzes (NetzDG)

2021 ◽  
Author(s):  
Katrin Giere
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Public Opinion ◽  
Scientific Research ◽  
Political Decision ◽  
Media Freedom ◽  
Penal Law ◽  
Political Decision Making

The influence on public opinion of social networks such as Facebook and Twitter regarding the process of political decision-making is constantly evolving. However, the discussion whether these networks are holders of the fundamental right of media freedom is still in its "infancy stage". This piece takes up this topic, which is practically relevant, but still lacks adequate scientific research. Against this background, the paper addresses the Network Enforcement Act (NetzDG) which came into effect in Germany on 1 October 2017. With this law, the federal legislature has imposed proactive inspection obligations on certain providers of social networks. Operators are now legally required to check contents to ensure it does not violate German penal law.

scholarly journals A Bio-Inspired Defensive Rumor Confinement Strategy in Online Social Networks

2021 ◽  
Vol 33 (1) ◽  
pp. 47-70
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L. D.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Propagation Model ◽  
Information Propagation ◽  
Control Approach ◽  
Rumor Propagation ◽  
Immunization Strategies ◽  
New Information ◽  
The Individual ◽  
Rumor Control

Online social networks (OSNs) are used to connect people and propagate information around the globe. Along with information propagation, rumors also penetrate across the OSNs in a massive order. Controlling the rumor propagation is utmost important to reduce the damage it causes to society. Educating the individual participants of OSNs is one of the effective ways to control the rumor faster. To educate people in OSNs, this paper proposes a defensive rumor control approach that spreads anti-rumors by the inspiration from the immunization strategies of social insects. In this approach, a new information propagation model is defined to study the defensive nature of true information against rumors. Then, an anti-rumor propagation method with a set of influential spreaders is employed to defend against the rumor. The proposed approach is compared with the existing rumor containment approaches and the results indicate that the proposed approach works well in controlling the rumors.

scholarly journals A New Geo-Propagation Model of Event Evolution Chain Based on Public Opinion and Epidemic Coupling

2020 ◽  
Vol 17 (24) ◽  
pp. 9235
Author(s):  
Yan Zhang ◽  
Nengcheng Chen ◽  
Wenying Du ◽  
Shuang Yao ◽  
Xiang Zheng
Keyword(s):  
Public Health ◽  
Public Opinion ◽  
Spatial Dimension ◽  
Real Space ◽  
Propagation Model ◽  
Health Events ◽  
Model Complex ◽  
Epidemic Area ◽  
Before And After ◽  
The Impact

The online public opinion is the sum of public views, attitudes and emotions spread on major public health emergencies through the Internet, which maps out the scope of influence and the disaster situation of public health events in real space. Based on the multi-source data of COVID-19 in the context of a global pandemic, this paper analyzes the propagation rules of disasters in the coupling of the spatial dimension of geographic reality and the dimension of network public opinion, and constructs a new gravity model-complex network-based geographic propagation model of the evolution chain of typical public health events. The strength of the model is that it quantifies the extent of the impact of the epidemic area on the surrounding area and the spread of the epidemic, constructing an interaction between the geographical reality dimension and online public opinion dimension. The results show that: The heterogeneity in the direction of social media discussions before and after the “closure” of Wuhan is evident, with the center of gravity clearly shifting across the Yangtze River and the cyclical changing in public sentiment; the network model based on the evolutionary chain has a significant community structure in geographic space, divided into seven regions with a modularity of 0.793; there are multiple key infection trigger nodes in the network, with a spatially polycentric infection distribution.

Modelling multi-topic information propagation in online social networks based on resource competition

2016 ◽  
Vol 43 (3) ◽  
pp. 342-355 ◽  
Author(s):  
Liyuan Sun ◽  
Yadong Zhou ◽  
Xiaohong Guan
Keyword(s):  
Social Networks ◽  
Network Structure ◽  
Online Social Networks ◽  
Resource Competition ◽  
Propagation Model ◽  
Small Scale ◽  
Model Parameters ◽  
Information Propagation ◽  
Practical Applications ◽  
The Impact

Understanding information propagation in online social networks is important in many practical applications and is of great interest to many researchers. The challenge with the existing propagation models lies in the requirement of complete network structure, topic-dependent model parameters and topic isolated spread assumption, etc. In this paper, we study the characteristics of multi-topic information propagation based on the data collected from Sina Weibo, one of the most popular microblogging services in China. We find that the daily total amount of user resources is finite and users’ attention transfers from one topic to another. This shows evidence on the competitions between multiple dynamical topics. According to these empirical observations, we develop a competition-based multi-topic information propagation model without social network structure. This model is built based on general mechanisms of resource competitions, i.e. attracting and distracting users’ attention, and considers the interactions of multiple topics. Simulation results show that the model can effectively produce topics with temporal popularity similar to the real data. The impact of model parameters is also analysed. It is found that topic arrival rate reflects the strength of competitions, and topic fitness is significant in modelling the small scale topic propagation.

scholarly journals Elements of Social Engineering Methodology Used During the COVID-19 Pandemic

2021 ◽  
pp. 5-18
Author(s):  
Oleksandr Trukhachov
Keyword(s):  
Social Networks ◽  
Public Opinion ◽  
Theoretical Study ◽  
Social Engineering ◽  
The Political ◽  
Traditional Media ◽  
Opinion Change ◽  
Political Landscape ◽  
History Of ◽  
Scientific Phenomenon

The article focuses on elements of social engineering (SI) that could be used by the states in their own interests during the COVID-19 pandemic. These elements were used to form negative public opinion, change the political landscape, and reduce citizens’ trust in their own governments. These elements are influence and persuasion. Traditional media and social networks play a major role in the use of these SI elements. SI has a long history of theoretical study as a scientific phenomenon. Practical elements of SI have a large arsenal, from government tools to influencing individuals. The article aims to demonstrate using SI elements, influence, and persuasion by the interested states and governments to obtain certain preferences for both foreign and domestic policies.

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