Modeling Multi-state Diffusion Process in Complex Networks: Theory and Applications
Refereed conference paper presented and published in conference proceedings


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其它資訊
摘要There is a growing interest to understand the fundamental principles of how epidemic, ideas or information spread over large networks (e.g., the Internet or online social networks). Conventional approach is to use SIS model (or its derivatives). However, these models usually are over-simplified and may not be applicable in realistic situations. In this paper, we propose a generalized SIS model by allowing intermediate states between susceptible and infected states. To analyze the diffusion process on large graphs, we use the "mean-field analysis technique" to determine which initial condition leads to or prevents information or virus outbreak. Numerical results show our methodology can accurately predict the behavior of the phase-transition process for various large graphs (e.g., complete graphs, random graphs or power-law graphs). We also extend our generalized SIS model to consider the interaction of two competing sources (i.e., competing products or virus-antidote modeling). We present the analytical derivation and show experimentally how different factors, e.g., transmission rates, recovery rates, number of states or initial condition, can affect the phase transition process and the final equilibrium. Our models and methodology can serve as an essential tool in understanding information diffusion in large networks.
著者Lin Y, Lui JCS, Jung K, Lim S
會議名稱9th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS)
會議開始日02.12.2013
會議完結日05.12.2013
會議地點Kyoto
會議國家/地區日本
出版年份2013
月份1
日期1
出版社IEEE
頁次501 - 508
電子國際標準書號978-1-4799-3211-5
語言英式英語
Web of Science 學科類別Computer Science; Computer Science, Information Systems; Engineering; Engineering, Electrical & Electronic

上次更新時間 2020-27-10 於 01:19