移动社交网络幂律分布特征及亲属关系判别

社交网络特征和用户关系是社交网络分析研究的重要内容。该文对移动社交网络中存在的幂律分布及用户亲属关系判别问题进行研究。在幂律分布的研究中,该文在度、连通子图规模及用户联系人数量的分布中找出存在的三个幂律分布,同时分析其中规律和结论,并与其他社交网络进行对比。在该文亲属关系判别研究中,通过提取用户通话行为的多种显著特征,采用GBDT(gradient boost decision tree)与LR (logistic regression)融合方法,提出一种用户亲属关系判别模型,并通过实验验证该模型能有效判别出用户间是否存在亲属关系,判别精确率达到81.01%。

Research on Power-law Distribution and Identification of Kinship in Mobile Social Network

Social network structure and user relationship are the important topicsin social network analysis. In this paper,we study the power-law distribution and the identification of kinship between users for the mobile social network. Three power law distributions are revealed in the distribution of degree,connected sub-graph scale and the user contacts,which are compared with other social networks. We study the identification model of kinship by using GBDT (Gradient Boost Decision Tree) and LR (Logistic Regression) fusion method by extracting a variety of salient features of user's call behavior. The experiment indicates that the model can determine whether there is a kinship between users at a precision of 81.01%.