Information spreading on metapopulation networks with heterogeneous contacting
Yanyi Nie,
Liming Pan,
Tao Lin and
Wei Wang
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Yanyi Nie: College of Computer Science, Sichuan University, Chengdu 610065, P. R. China
Liming Pan: School of Computer Science and Technology, Nanjing Normal University, Jiangsu 210023, P. R. China
Tao Lin: College of Computer Science, Sichuan University, Chengdu 610065, P. R. China
Wei Wang: School of Public Health and Management, Chongqing Medical University, Chongqing 400016, P. R. China
International Journal of Modern Physics C (IJMPC), 2022, vol. 33, issue 03, 1-13
Abstract:
Extensive real-data reveals that individuals exhibit heterogeneous contacting frequency in social systems. We propose a mathematical model to investigate the effects of heterogeneous contacting for information spreading in metapopulation networks. In the proposed model, we assume the number of contacting (NOC) distribution follows a specific distribution, including the normal, exponential, and power-law distributions. We utilize the Markov chain method to study the information spreading dynamics and find that mean and variance display no significant effect on the outbreak threshold for all the considered distributions. Under the same values of NOC distribution’s mean and variance, the information prevalence is largest when the distribution of NOC follows the normal distribution and second-largest for the exponential distribution, the smallest for the power-law distribution. When the distribution of NOC obeys the normal distribution, experimental results show that the information prevalence will decrease with individual contact ability heterogeneity. We observe similar phenomena when the distribution of NOC follows a power-law and exponential distribution. Furthermore, a larger mean of individual contact capacity distribution will result in higher information prevalence.
Keywords: information spreading; metapopulation model; heterogenous contacting (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)
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DOI: 10.1142/S0129183122500310
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