Читать книгу Intelligent Data Analytics for Terror Threat Prediction - Группа авторов - Страница 49

This observation gives limited information as discussed earlier in Section 1.5.1.2.2. It is useful for single rumor source detection on social networks, if multiple snapshots are taken in various time intervals. Single snapshot gives limited information about network and states of nodes whereas multiple snapshots give more information about these. Single source detection by applying rumor centrality metric and multiple observations is discussed [37]. They consider tree-like network and used SI model for rumor diffusion, they proves that multiple observations always improve detectable performance. Even two independent snapshot observations increases probability of source detection compare to single snapshot observation. The authors shown that source detection performance increases for multiple observations and decreases with number of infected nodes. After multiple observations use maximum likelihood estimator to find rumor centrality and from it to find rumor source in tree-like network and graph network. Graph network uses BFS technique to transform graph into BFS tree as discussed in above section. The problem in snapshot observation is if SIR model is used for information diffusion, it cannot distinguish between susceptible and recovered nodes.