Journal on Communications ›› 2016, Vol. 37 ›› Issue (10): 40-47.doi: 10.11959/j.issn.1000-436x.2016194

• Papers • Previous Articles     Next Articles

Influence diffusion model based on affinity of dynamic social network

Yun-fang CHEN1,Tao XIA1,2,Wei ZHANG1,Jin LI3   

  1. 1 School of Computer Science and Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
    2 Jining Branch of China Telecom.,Jining 272000,China
    3 School of Public Administration and Communication,Beijing University of Information Science and Technology,Beijing 100192,China
  • Online:2016-10-25 Published:2016-10-25
  • Supported by:
    The National Natural Science Foundation of China;Humanistic and Social Science Research Plan Project of Beijing Municipal Education Commission

Abstract:

Recently,influence maximization model is a hot issue in the field of social network influence,while the traditional independent cascade model is generally based on static network with a fixed value of activation probability.DDIC model,which was a dynamic network influence diffusion model with attenuation factor was proposed.It calculated the activation probability between nodes via affinity propagation,and according with dynamic segmentation of social network time slice,calculation of influence on proliferation of next time slice with the current time slice of activation probability performance decay.The experimental results show that the nodes in the DDIC model have more chances to active the neighbor and the average probability of activing of the DDIC model is higher.Further experiments show that influence value via computing with affinity propagation can reflect the process of the spread model more accurately.

Key words: dynamic social network, influence diffusion, affinity propagation

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