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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 6/2019

15-05-2018 | Original Article

A game theory-based network rumor spreading model: based on game experiments

Authors: Fengming Liu, Mingcai Li

Published in: International Journal of Machine Learning and Cybernetics | Issue 6/2019

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Abstract

This paper considers the relation between a rumor maker and many disseminators as a game and sets up Explosion-Trust (ET) Game Model. This model regards rumor explosion degree and trust degree of source node as influential factors of rumor making and spreading. The purpose of on both sides of a game is to obtain a maximum benefit. Based on ET model, we make experiments imitating the mode of information dissemination in social networks. We find rumor makers don’t make rumors with quite a high explosion degree because others will doubt the truth of such rumor bringing a low transmission rate. This paper finds an optimal value for rumor spreading by experiments and on what condition trust degree will have an important impact on rumor spreading. Based on experiment results, the authors sum up the universal characteristics of rumors spread widely. Conclusions will be used to detect rumors.
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Metadata
Title
A game theory-based network rumor spreading model: based on game experiments
Authors
Fengming Liu
Mingcai Li
Publication date
15-05-2018
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 6/2019
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-018-0826-5

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