Author: Na Zhao; Jian Wang; Yong Yu; Jun-Yan Zhao; Duan-Bing Chen
Title: Spreading predictability in complex networks Document date: 2020_1_28
ID: 635lbedk_18
Snippet: Besides synthetic networks, we also analyze the predictability χ and correlation Ï 164 on 11 real networks. The properties and analysis results on these real networks are 165 shown in Table 1 Up to now, most of researches mainly focus on the infection scale or threshold when 173 they study the spreading dynamics in complex networks. However, following questions 174 may be more important and interesting: Which nodes will be infected in the futur.....
Document: Besides synthetic networks, we also analyze the predictability χ and correlation Ï 164 on 11 real networks. The properties and analysis results on these real networks are 165 shown in Table 1 Up to now, most of researches mainly focus on the infection scale or threshold when 173 they study the spreading dynamics in complex networks. However, following questions 174 may be more important and interesting: Which nodes will be infected in the future presented a probability based prediction model to predict the infection nodes. Three 177 synthetic and eleven real networks are used to evaluate the proposed model.
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