Community Structure-based Re-ranking Information Influence Maximization Algorithm for Typhoon Disasters

Zufeng Zhong, Hongyan Yang

Ekoloji, 2019, Issue 107, Pages: 453-462, Article No: e107054


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This paper proposes a new community structure-based influence maximization algorithm (CSRR) based on the topological structure of diffusion networks for typhoon disasters. We developed the proposed algorithm by using pre-existing community detection algorithms to detect the community structures hidden in the networks and identify the TOP-M nodes which span a relatively large number of communities; We found the TOP-K nodes at large distances and used them as the initial diffusers of influence through re-ranking of the M nodes. A typhoon disaster event in the Leizhou Peninsula, China, is used as an example to validate the effectiveness and feasibility of the proposed Algorithm. Our test results show that this algorithm provides higher diffusion speed and larger diffusion range than traditional-influence maximization algorithms in the typhoon disaster.


typhoon disasters, online social network, influence, community structure, re-ranking, China


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