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	Using Structural Features to Characterize Social Ties
	Zuo, Yang ; Zhang, Kan
	2016
关键词	social networks social ties structural features logistic regression model NETWORKS STRENGTH
英文摘要	Social ties are crucial to understand group behaviors in social networks. Since users rarely label their friends explicitly in social networks, characterizing social ties and understanding their strength of these ties is a critical problem. In this paper, we apply logistic regression model to infer the strength of social ties based on the structural features of social networks, and we produce two new features: cliqueness and linkness. In addition, we use the Strong Triadic Closure principle as a global constraint. We test our model on four different datasets: Facebook, American College Football, Les Miserables and Zachary's Karate Club. Experimental results demonstrate that the performance of our model with structural features is satisfactory.; State Key Development Program of Basic Research of China (973) [2013cb329600]; National Natural Science Foundation of China [61372191, 61572492]; CPCI-S(ISTP); 235-242
语种	英语
出处	1st IEEE International Conference on Data Science in Cyberspace (DSC)
DOI标识	10.1109/DSC.2016.63
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470083]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zuo, Yang,Zhang, Kan. Using Structural Features to Characterize Social Ties. 2016-01-01.

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