An SEI3R information propagation control algorithm with structural hole and high influential infected nodes in social networks

The iterative propagation of information between nodes will strengthen the connection strength between nodes, and the network can evolve into different groups according to difference edge strength. Based on this observation, we present the user engagement to quantify the influences of users different propagation modes to network propagation, and construct weight network to simulate real social network, and proposed the community detection method in social networks based on information propagation and user engagement. Our method can produce different scale communities and overlapping community. We also applied our method to real-world social networks. The experiment proved that the network spread and the community division interact with each other. The community structure is significantly different in the network propagation of different scales.

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

Journal of Organizational and End User Computing ◽

10.4018/joeuc.2021010103 ◽

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.

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Coupling entropy of co-processing model on social networks

Modern Physics Letters B ◽

10.1142/s0217984915501493 ◽

2015 ◽

Vol 29 (25) ◽

pp. 1550149

Author(s):

Zhanli Zhang

Keyword(s):

Social Networks ◽

Information Flow ◽

Structural Characteristics ◽

Time Lag ◽

Optimal Routing ◽

Information Propagation ◽

Time Processing ◽

Scale Free ◽

Routing Strategy ◽

Processing Ability

Coupling entropy of co-processing model on social networks is investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. In order to understand the evolution of the co-processing and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the coupling entropy comprehending the structural characteristics and information propagation on social network. Based on the analysis of the co-processing model, we analyze the coupling impact of the structural factor and information propagating factor on the coupling entropy, where the analytical results fit well with the numerical ones on scale-free social networks.

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