Seminar Vol. 157

Title: Portal Nodes Screening for Large Scale Social Networks

Speaker: Xuening Zhu, Fudan University

Time: May 20th, 2019 10:00–11:30

Venue: Conference Room 106B, Zhonghui Building (IESR, JNU College of Economics)

About the speaker:

Xuening Zhu is an Assistant Professor in the School of Data Science, Fudan University. She received a Ph.D. in Statistics from Peking University in 2017. During 2017–2018 she worked as a Postdoctoral Research Assistant in the Department of Statistics, Penn State University. Xuening Zhu's research interests are mainly in network/spatial data modelling and business statistics. She has published her work in such journals as Annals of Statistics, Journal of Econometrics, and Statistica Sinica.

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.