Dynamic social network active influence maximization algorithm based on Coulomb force model
The problem of maximizing influence has become an important research content in social networks,and its influence propagation model and solving algorithm are the key core issues.In order to improve the accuracy of predicting the propagation results,the dynamic change of the number of activated nodes...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2020-06-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020162/ |
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| _version_ | 1841530663378878464 |
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| author | Min LU Guanglu CHEN Xiaohui YANG Chunlan HUANG Guangxue YUE |
| author_facet | Min LU Guanglu CHEN Xiaohui YANG Chunlan HUANG Guangxue YUE |
| author_sort | Min LU |
| collection | DOAJ |
| description | The problem of maximizing influence has become an important research content in social networks,and its influence propagation model and solving algorithm are the key core issues.In order to improve the accuracy of predicting the propagation results,the dynamic change of the number of activated nodes and the trust relationship between the nodes during the propagation process were introduced to improve the IC model.Combining the similarity between social influence and Coulomb force,a dynamic based on trust relationship was proposed,a dynamic social coulomb forces based on trust relationships (DSC-TR) model was proposed,and an optimized random greedy (RG-DPIM) algorithm was constructed to solve the problem of maximum impact.Simulation results show that the prediction accuracy of the DSC-TR model is obviously better than that of SC-B and IC models.The performance of RG-DPIM algorithm is obviously better than that of G-DPIM,IPA and TDIA algorithms. |
| format | Article |
| id | doaj-art-4d473a59c03e4e32bdbcf800d64cc119 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2020-06-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-4d473a59c03e4e32bdbcf800d64cc1192025-01-15T03:00:35ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012020-06-013610711859582710Dynamic social network active influence maximization algorithm based on Coulomb force modelMin LUGuanglu CHENXiaohui YANGChunlan HUANGGuangxue YUEThe problem of maximizing influence has become an important research content in social networks,and its influence propagation model and solving algorithm are the key core issues.In order to improve the accuracy of predicting the propagation results,the dynamic change of the number of activated nodes and the trust relationship between the nodes during the propagation process were introduced to improve the IC model.Combining the similarity between social influence and Coulomb force,a dynamic based on trust relationship was proposed,a dynamic social coulomb forces based on trust relationships (DSC-TR) model was proposed,and an optimized random greedy (RG-DPIM) algorithm was constructed to solve the problem of maximum impact.Simulation results show that the prediction accuracy of the DSC-TR model is obviously better than that of SC-B and IC models.The performance of RG-DPIM algorithm is obviously better than that of G-DPIM,IPA and TDIA algorithms.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020162/social networkinfluence maximizationCoulomb forcediffusion modeltrust relationship |
| spellingShingle | Min LU Guanglu CHEN Xiaohui YANG Chunlan HUANG Guangxue YUE Dynamic social network active influence maximization algorithm based on Coulomb force model Dianxin kexue social network influence maximization Coulomb force diffusion model trust relationship |
| title | Dynamic social network active influence maximization algorithm based on Coulomb force model |
| title_full | Dynamic social network active influence maximization algorithm based on Coulomb force model |
| title_fullStr | Dynamic social network active influence maximization algorithm based on Coulomb force model |
| title_full_unstemmed | Dynamic social network active influence maximization algorithm based on Coulomb force model |
| title_short | Dynamic social network active influence maximization algorithm based on Coulomb force model |
| title_sort | dynamic social network active influence maximization algorithm based on coulomb force model |
| topic | social network influence maximization Coulomb force diffusion model trust relationship |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020162/ |
| work_keys_str_mv | AT minlu dynamicsocialnetworkactiveinfluencemaximizationalgorithmbasedoncoulombforcemodel AT guangluchen dynamicsocialnetworkactiveinfluencemaximizationalgorithmbasedoncoulombforcemodel AT xiaohuiyang dynamicsocialnetworkactiveinfluencemaximizationalgorithmbasedoncoulombforcemodel AT chunlanhuang dynamicsocialnetworkactiveinfluencemaximizationalgorithmbasedoncoulombforcemodel AT guangxueyue dynamicsocialnetworkactiveinfluencemaximizationalgorithmbasedoncoulombforcemodel |