scholarly journals Propagation Models for Trust and Distrust in Social Networks

2005 ◽  
Vol 7 (4-5) ◽  
pp. 337-358 ◽  
Author(s):  
Cai-Nicolas Ziegler ◽  
Georg Lausen
Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Xue Yang ◽  
Zhiliang Zhu ◽  
Hai Yu ◽  
Yuli Zhao

We study herein the problem of the location of the information propagation source in social networks based on the network topology and a set of observations. We propose a concise and novel method to accurately locate the source of information using naming game theory. This study introduces the design of a dynamic deployment method that reduces considerably the number of observations and the time needed to locate the source. Moreover, it calculates the probability of each node that acts as a source based on the information provided by observations. This method can be potentially applied to various information propagation models. The simulation results reveal that the method is able to estimate the information source within a small number of hops from the true source.


2014 ◽  
Vol 15 (1) ◽  
pp. 125-134
Author(s):  
Jong-Hwan Kong ◽  
Ik Kyun Kim ◽  
Myung-Mook Han

Author(s):  
Rong Jin ◽  
Weili Wu

Recent years have seen various rumor diffusion models being assumed in detection of rumor source research of the online social network. Diffusion model is arguably considered as a very important and challenging factor for source detection in networks, but it is less studied. This paper provides an overview of three representative schemes of modeling the pattern of rumor propagation as well as three major schemes of rumor source estimator in the Independent Cascade-based model, the Epidemic-based model, and the Learning-based model, respectively, since their inception a decade ago.


2015 ◽  
Vol 181 ◽  
pp. 65-79 ◽  
Author(s):  
Jason Vallet ◽  
Hélène Kirchner ◽  
Bruno Pinaud ◽  
Guy Melançon

Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi

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