Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes
For understanding and controlling spreading in complex networks, identifying the most influential nodes, which can be applied to disease control, viral marketing, air traffic control, and many other fields, is of great importance. By taking the effect of the spreading rate on information entropy int...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5554322 |
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| _version_ | 1832568493376012288 |
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| author | Linfeng Zhong Yu Bai Yan Tian Chen Luo Jin Huang Weijun Pan |
| author_facet | Linfeng Zhong Yu Bai Yan Tian Chen Luo Jin Huang Weijun Pan |
| author_sort | Linfeng Zhong |
| collection | DOAJ |
| description | For understanding and controlling spreading in complex networks, identifying the most influential nodes, which can be applied to disease control, viral marketing, air traffic control, and many other fields, is of great importance. By taking the effect of the spreading rate on information entropy into account, we proposed an improved information entropy (IIE) method. Compared to the benchmark methods in the six different empirical networks, the IIE method has been found with a better performance on Kendall’s Tau and imprecision function under the Susceptible Infected Recovered (SIR) model. Especially in the Facebook network, Kendall’s Tau can grow by 120% as compared with the original IE method. And, there is also an equally good performance in the comparative analysis of imprecise functions. The imprecise functions’ value of the IIE method is smaller than the benchmark methods in six networks. |
| format | Article |
| id | doaj-art-46d234fe74ee49ab87bbb8a8bd554eb4 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-46d234fe74ee49ab87bbb8a8bd554eb42025-02-03T00:58:59ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55543225554322Information Entropy Based on Propagation Feature of Node for Identifying the Influential NodesLinfeng Zhong0Yu Bai1Yan Tian2Chen Luo3Jin Huang4Weijun Pan5Civil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaSchool of Science, Southwest Petroleum University, Chengdu 610500, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaCivil Aviation Flight University of China, Guanghan 618307, ChinaFor understanding and controlling spreading in complex networks, identifying the most influential nodes, which can be applied to disease control, viral marketing, air traffic control, and many other fields, is of great importance. By taking the effect of the spreading rate on information entropy into account, we proposed an improved information entropy (IIE) method. Compared to the benchmark methods in the six different empirical networks, the IIE method has been found with a better performance on Kendall’s Tau and imprecision function under the Susceptible Infected Recovered (SIR) model. Especially in the Facebook network, Kendall’s Tau can grow by 120% as compared with the original IE method. And, there is also an equally good performance in the comparative analysis of imprecise functions. The imprecise functions’ value of the IIE method is smaller than the benchmark methods in six networks.http://dx.doi.org/10.1155/2021/5554322 |
| spellingShingle | Linfeng Zhong Yu Bai Yan Tian Chen Luo Jin Huang Weijun Pan Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes Complexity |
| title | Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes |
| title_full | Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes |
| title_fullStr | Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes |
| title_full_unstemmed | Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes |
| title_short | Information Entropy Based on Propagation Feature of Node for Identifying the Influential Nodes |
| title_sort | information entropy based on propagation feature of node for identifying the influential nodes |
| url | http://dx.doi.org/10.1155/2021/5554322 |
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