Enhanced by mobility? Effect of users’ mobility on information diffusion in coupled online social networks

Yanan Wang, Jun Wang, Ruilin Zhang and Ou Liu

Physica A: Statistical Mechanics and its Applications, 2022, vol. 607, issue C

Abstract: Online social networks have gradually become crucial tools for users to exchange information. Two characteristics of online social networks should be underlined: first, individuals can freely leave or stay; second, information diffusion is more common on coupled online social platforms. However, very few research combines the above two aspects when studying the information diffusion in online social networks. Therefore, we establish an in-out-unacquired2-acquired 2-rejected2 (IO-S2P2R2) information diffusion model which investigates the time evolution of three types of users considering users’ mobility in coupled online social networks using mean-field theory. We analyze the theoretical threshold of information diffusion via linear analysis and find that the information diffusion threshold is related to the maximum eigenvalue of the super adjacency matrix. Moreover, by comparing the mean-field method with the Monte Carlo method, the consistency of the simulation results is obtained, which verifies the scientificity of our model. The results demonstrate the consistency of linear analysis and simulation experiments. Besides, based on the existing data sets, information diffusion rates and users’ mobility rates are positively correlated with the range of information diffusion, while information decline rates are negatively correlated with the range of information diffusion through the sensitivity analysis of parameters.

Keywords: Information diffusion; Users’ mobility; Coupled online social networks; Mean-field theory; Friendfeed (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007592

DOI: 10.1016/j.physa.2022.128201

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