A Trend Prediction Method for Misinformation Spreading with Time Delay Effect

Author:

Zhang Chengxin1,Lin Yaguang1,Wang Xiaoming1,Hao Yumeng1

Affiliation:

1. School of Computer Science Shaanxi Normal University Shaanxi Xi'an 710119 China

Abstract

Online social networks (OSNs) provide a platform for users to express opinions, discuss events and exchange ideas. However, the spread of misinformation in OSNs will interfere with users' judgment of useful information and may even cause significant economic losses to society. Exploring the spreading mechanism of misinformation in online social networks is the basis of eliminating the harm brought by misinformation to the network. Firstly, considering the influence of time delay on information spreading in real life, we propose a new misinformation spreading model to explore its spreading mechanism and describe its spreading process. Secondly, we provide the predictive method for studying the spread of misinformation in OSNs and theoretically demonstrate the stability of equilibrium points in the proposed information spreading model. Finally, we conduct simulation experiments based on a real dataset. The results show that compared to the benchmark model, our proposed model can reasonably explore the spreading mechanism and accurately predict the spreading trend of misinformation. Our proposed model and method can further establish a foundation for fast and effectively controlling the spread of misinformation and improving the controllability and efficiency of network communication and information spread. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering

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