Ranking Influential Nodes in Complex Networks with Information Entropy Method
نویسندگان
چکیده
منابع مشابه
Locating influential nodes in complex networks
Understanding and controlling spreading processes in networks is an important topic with many diverse applications, including information dissemination, disease propagation and viral marketing. It is of crucial importance to identify which entities act as influential spreaders that can propagate information to a large portion of the network, in order to ensure efficient information diffusion, o...
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Identifying influential nodes that lead to faster and wider spreading in complex networks is of theoretical and practical significance. The degree centrality method is very simple but of little relevance. Global metrics such as betweenness centrality and closeness centrality can better identify influential nodes, but are incapable to be applied in large-scale networks due to the computational c...
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Designing node influence ranking algorithms can provide insights into network dynamics, functions and structures. Increasingly evidences reveal that node's spreading ability largely depends on its neighbours. We introduce an iterative neighbourinformation gathering (Ing) process with three parameters, including a transformation matrix, a priori information and an iteration time. The Ing process...
متن کاملIdentifying influential nodes in complex networks with community structure
Article history: Received 2 July 2012 Received in revised form 14 January 2013 Accepted 16 January 2013 Available online 26 January 2013
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Recently an increasing amount of research is devoted to the question of how the most influential nodes (seeds) can be found effectively in a complex network. There are a number of measures proposed for this purpose, for instance, high-degree centrality measure reflects the importance of the network topology and has a reasonable runtime performance to find a set of nodes with highest degree, but...
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ژورنال
عنوان ژورنال: Complexity
سال: 2020
ISSN: 1076-2787,1099-0526
DOI: 10.1155/2020/5903798