经济与社会研究院SEMINAR第156期

题目：Portal Nodes Screening for Large Scale Social Networks

主讲人：朱雪宁，复旦大学

时间：2019年5月20日，10:00-11:30

地点：暨南大学中惠楼106B室

主讲人简介：

朱雪宁，复旦大学大数据学院青年副研究员，2017年获得北京大学光华管理学院商务统计与经济计量系博士学位，之后在美国宾夕法尼亚州立大学从事博士后研究工作，并于2018年入职复旦大学大数据学院。入选2019年度上海市青年科技英才扬帆计划。主要研究领域为社交网络分析、高维数据建模等，研究成果发表于Annals of Statistics, Journal of Econometrics, Statistica Sinica等国际顶级期刊。

Abstract:

Network autoregression model (NAM), as a powerful tool to study user social behaviors on large scale social networks, has drawn great attention in recent years. In this paper, we are interested in identifying the influential users (i.e., portal nodes) in a social network under the framework of NAM. Especially, we consider the autoregression model that allows to have a heterogenous and sparse network effect coefficients. Therefore, the portal nodes take influential powers which are corresponding to the nonzero network effect coefficients. A screening procedure is designed to screen out the portal nodes and the strong screening consistency is established theoretically. A quasi maximum likelihood method is applied to estimate the influential powers. The asymptotic normality of the resulting estimator is established. Further selection procedure is given by taking advantage of the local linear approximation algorithm. Extensive numerical studies are conducted by using a Sina Weibo dataset for illustration purpose.