scholarly journals SETQR Propagation Model for Social Networks

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 127533-127543 ◽  
Author(s):  
Yuexia Zhang ◽  
Ziyang Chen
Keyword(s):  
Social Networks ◽  
Propagation Model

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.

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 Key Node Discovery Algorithm Based on Multiple Relationships and Multiple Features in Social Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xianyong Li ◽  
Ying Tang ◽  
Yajun Du ◽  
Yanjie Li
Keyword(s):  
Social Networks ◽  
Propagation Model ◽  
Multiple Relationships ◽  
Information Propagation ◽  
Multiple Features ◽  
Relational Networks ◽  
Discovery Algorithms ◽  
Relational Network ◽  
Single Relation ◽  
Key Nodes

The key nodes play important roles in the processes of information propagation and opinion evolution in social networks. Previous work rarely considered multiple relationships and features into key node discovery algorithms at the same time. Based on the relational networks including the forwarding network, replying network, and mentioning network in a social network, this paper first proposes an algorithm of the overlapping user relational network to extract different relational networks with same nodes. Integrated with these relational networks, a multirelationship network is established. Subsequently, a key node discovery (KND) algorithm is presented on the basis of the shortest path, degree centrality, and random walk features in the multirelationship network. The advantages of the proposed KND algorithm are proved by the SIR propagation model and the normalized discounted cumulative gain on the multirelationship networks and single-relation networks. The experiment’s results show that the proposed KND method for finding the key nodes is superior to other baseline methods on different networks.

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.

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

2019 ◽  
Vol 23 (2) ◽  
pp. 1261-1273 ◽  
Author(s):  
Weimin Li ◽  
Yuting Fan ◽  
Jun Mo ◽  
Wei Liu ◽  
Can Wang ◽  
...  
Keyword(s):  
Social Networks ◽  
Influence Maximization ◽  
Propagation Model ◽  
Velocity Attenuation

Global Stability and Bifurcation Analysis of a Rumor Propagation Model with Two Discrete Delays in Social Networks

2020 ◽  
Vol 30 (12) ◽  
pp. 2050175
Author(s):  
Linhe Zhu ◽  
Xuewei Wang ◽  
Zhengdi Zhang ◽  
Shuling Shen
Keyword(s):  
Social Networks ◽  
Global Stability ◽  
Equilibrium Points ◽  
Propagation Model ◽  
Logistic Growth ◽  
Positive Equilibrium ◽  
Normal Form Theory ◽  
Center Manifold Theorem ◽  
Rumor Propagation ◽  
Discrete Delays

In this paper, we improve an Ignorant-Lurker-Spreader-Removal (ILSR) rumor propagation model as in [Yang et al., 2019] in social networks with consideration to Logistic growth and two discrete delays. First, we prove the existence of equilibrium points by calculating the basic reproduction number according to the next generation matrix. Regarding the two discrete delays as bifurcating parameters, the local asymptotical stability and Hopf bifurcation of the positive equilibrium point are discussed for six different scenarios by analyzing the characteristic equations of linearized systems. Applying the normal form theory and the center manifold theorem, some important conclusions about the stability and direction of bifurcating periodic solution are given when the two time delays are equal. Subsequently we study the global stability of the equilibrium points by constructing Lyapunov functions when the two delays disappear. Finally, we verify the conclusions through numerical simulations and perform sensitivity analysis on the basic reproduction numbers.

Dynamics of a Rumor Propagation Model with Stochastic Perturbation On Homogeneous Social Networks

2021 ◽  
Author(s):  
Yuhuai Zhang ◽  
Jianjun Zhu
Keyword(s):  
Social Networks ◽  
Transmission Rate ◽  
Rapid Development ◽  
Stochastic Perturbation ◽  
Propagation Model ◽  
Rumor Propagation ◽  
Long Time ◽  
Global Positive Solution ◽  
Stochastic Properties

Abstract The rapid development of information society highlights the important role of rumors in social communication, and its propagation has a significant impact on human production and life. The investigation of the influence of uncertainty on rumor propagation is an important issue in the current communication study. Due to incomprehension about others and the stochastic properties of the users' behavior, the transmission rate between individuals on social network platforms is usually not a constant value. In this paper, we propose a new rumor propagation model on homogeneous social networks from the deterministic structure to the stochastic structure. Firstly, a unique global positive solution of rumor propagation model is obtained. Then, we verify that the extinction and persistence of stochastic rumor propagation model are restricted by some conditions. IfR *0< 1 and the noise intensity s i (i = 1,2,3) satisfies some certain conditions, rumors will extinct with a probability one. If R *0 > 1, rumor-spreading individuals will continue to exist in the system, which means the rumor will prevail for a long time. Finally, through some numerical simulations, the validity and rationality of the theoretical analysis are effectively verified.

A Novel Rumor Propagation Model on Social Networks

2016 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Junjie Chen ◽  
Weili Wu ◽  
Ailian Wang
Keyword(s):  
Social Networks ◽  
Propagation Model ◽  
Rumor Propagation
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