Modeling rumor propagation and mitigation across multiple social networks

Chenxu Wang, Gaoshuai Wang, Xiapu Luo and Hui Li

Physica A: Statistical Mechanics and its Applications, 2019, vol. 535, issue C

Abstract: Social media has become an essential part of people’s lives with the rapid development of the Internet and mobile technologies. Although social media has brought great convenience for people to communicate, it also powers misinformation such as rumors to reach more people in a short time than ever before. Moreover, social networks are interconnected with each other since users may join multiple social media simultaneously, which makes the situation even worse. Therefore, it is urgent to model the propagation of rumors across multiple social media and investigate mitigation strategies. In this paper, we propose an improved energy model to characterize the propagation of rumors on social networks quantitatively. We also introduce negative energy to simulate the mitigation process of rumors. Finally, we apply our proposed models to study the impact of the linkage rates on rumor propagation across multiple social networks. We conduct extensive experiments based on real social networks to evaluate the impacts of model parameters, network structures, and effective linkage rates. The experimental results demonstrate the effectiveness of our model in characterizing rumor propagation on multiple social networks. We also obtain valuable findings for effective rumor mitigation.

Keywords: Rumor propagation; Energy model; Rumor mitigation; Negative energy; Multilayer networks (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119312993

DOI: 10.1016/j.physa.2019.122240

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