Social Relationship Analysis Model Based onthe Principle of Maximum Entropy

XIAO Yunpeng; YANG Guang; LIU Yanbing; WU Bin

doi:10.11999/JEIT160605

Volume 39 Issue 4

Apr. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(4): 778-784

XIAO Yunpeng, YANG Guang, LIU Yanbing, WU Bin. Social Relationship Analysis Model Based onthe Principle of Maximum Entropy[J]. Journal of Electronics & Information Technology, 2017, 39(4): 778-784. doi: 10.11999/JEIT160605

Citation:

XIAO Yunpeng, YANG Guang, LIU Yanbing, WU Bin. Social Relationship Analysis Model Based onthe Principle of Maximum Entropy[J]. Journal of Electronics & Information Technology, 2017, 39(4): 778-784. doi: 10.11999/JEIT160605

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Social Relationship Analysis Model Based onthe Principle of Maximum Entropy

doi: 10.11999/JEIT160605

1.
(Chongqing Engineering Laboratory of Internet and Information Security, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)
2.
(The Intelligent Communication Software and Multimedia Key Laboratory of Beijing, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Funds:

The National 973 Program of China (2013CB 329606), The National Natural Science Foundation of China (61272400), Chongqing Youth Innovative Talent Project (cstc2013 kjrc-qnrc40004), Ministry of Education of China and China Mobile Research Fund (MCM20130351), Chongqing Graduate Research and Innovation Project (CYS14146), Science and Technology Research Program of the Chongqing Municipal Education Committee (KJ1500425), WenFeng Foundation of CQUPT (WF201403)

Received Date: 2016-06-07
Rev Recd Date: 2016-11-30
Publish Date: 2017-04-19

Abstract

Abstract

Within the evolution and development of social networks, the establishment of relationships among the users is affected by various factors. By analyzing user behavior data and relationship data in social network, this study tries to detect the key factors that affect the formation of relationship among users. Firstly, considering the complex driving factors for the user relationship establishment, the factors are extracted and the impact factor functions are defined from personal attributes, friendships and community driving. Secondly, in order to quantify driving factors and assign weight, a user relationship analysis model based on the principle of maximum entropy is proposed. The model is, when choosing features, characterized by its independence from?the association among features, and can also quantify the strength of various factors that drive users to establish relationship. Furthermore, the key factors that affect the user relationship can be detected and the development trend of user relationship can be analyzed. Experimental results reveal that the proposal model can not only quantify the strength of each factor that drives relationship establishment, it can also predict the user relationship effectively.
- Social network,
- User relationship,
- Situation analysis,
- Principle of maximum entropy

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References(21)

References

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