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- W2785682739 abstract "One of essential issues that attract most scholars' concern is to identify a set of influential spreaders in a large network so that they can spread influence to the largest range on the network with a little effort. Traditional methods for mining influential nodes on the complex networks mostly focus on unweighted undirected networks, which fail to reveal a lot of details on the real systems. However, researches for detection important individuals on the weighted directed network are few, but also ignore some of essential influencer due to merely consider edge direction as a factor impact node's importance. Based on the existing research, we distinguish the contribution of in-degree and out-degree to the importance of the node and put forward a method on the weighted directed network based on ClusterRank to identify the influential spreaders by considering the influence of both edge weights and direction to the node importance. The results show that the important nodes identifying by IO-ClusterRank algorithm has similar influence as other methods on networks which distribution of in-degree and out-degree is approximately symmetric, but have more influence ability and faster spreading speed on other kinds of networks. Furthermore, it still remain a lower time complexity same as original method because of unchanged local characteristics." @default.
- W2785682739 created "2018-02-23" @default.
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- W2785682739 date "2017-12-01" @default.
- W2785682739 modified "2023-10-02" @default.
- W2785682739 title "Identifying Influential Spreaders on Weighted Networks Based on ClusterRank" @default.
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- W2785682739 doi "https://doi.org/10.1109/iscid.2017.222" @default.
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