社会化媒体
计算机科学
扩散
业务
知识管理
互联网
社交网络(社会语言学)
作者
Yun Liu,Su-Meng Diao,Yi-Xiang Zhu,Qing Liu
出处
期刊:Physica A-statistical Mechanics and Its Applications
日期:2016-11-01
卷期号:461: 543-553
被引量:26
标识
DOI:10.1016/j.physa.2016.06.080
摘要
Abstract In online social media, opinion divergences and differentiations generally exist as a result of individuals’ extensive participation and personalization. In this paper, a Susceptible–Hesitated–Infected–Removed (SHIR) model is proposed to study the dynamics of competitive dual information diffusion. The proposed model extends the classical SIR model by adding hesitators as a neutralized state of dual information competition. It is both hesitators and stable spreaders that facilitate information dissemination. Researching on the impacts of diffusion parameters, it is found that the final density of stiflers increases monotonically as infection rate increases and removal rate decreases. And the advantage information with larger stable transition rate takes control of whole influence of dual information. The density of disadvantage information spreaders slightly grows with the increase of its stable transition rate, while whole spreaders of dual information and the relaxation time remain almost unchanged. Moreover, simulations imply that the final result of competition is closely related to the ratio of stable transition rates of dual information. If the stable transition rates of dual information are nearly the same, a slightly reduction of the smaller one brings out a significant disadvantage in its propagation coverage. Additionally, the relationship of the ratio of final stiflers versus the ratio of stable transition rates presents power characteristic.
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