A Statistical Model for Social Network Labeling

22 Pages Posted: 7 Sep 2015

See all articles by Danyang Huang

Danyang Huang

Peking University

Jun Yin

Peking University

Tao Shi

Ohio State University (OSU)

Hansheng Wang

Peking University - Guanghua School of Management

Date Written: July 26, 2015

Abstract

We consider a social network from which one observes not only network structure (i.e., nodes and edges) but also a set of labels (or tags, keywords) for each node (or user). These labels are self-created and closely related to the user's career status, life style, personal interests, and many others. Thus, they are of great interest for online marketing. To model their joint behavior with network structure, a complete data model is developed. The model is based on the classical p1 model but allows the reciprocation parameter to be label-dependent. By focusing on connected pairs only, the complete data model can be generalized into a conditional model. Compared with the complete data model, the conditional model specifies only the conditional likelihood for the connected pairs. As a result, it suffers less risk from model mis-specification. Furthermore, because the conditional model involves connected pairs only, the computational cost is much lower. The resulting estimator is consistent and asymptotically normal. Depending on the network sparsity level, the convergence rate could be different. To demonstrate its finite sample performance, numerical studies (based on both simulated and real datasets) are presented.

Keywords: Conditional Maximum Likelihood; Maximum Likelihood; p1 Model; Sina Weibo; Large-Scale Network

JEL Classification: C30

Suggested Citation

Huang, Danyang and Yin, Jun and Shi, Tao and Wang, Hansheng, A Statistical Model for Social Network Labeling (July 26, 2015). Available at SSRN: https://ssrn.com/abstract=2636120 or http://dx.doi.org/10.2139/ssrn.2636120

Danyang Huang

Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

Jun Yin

Peking University

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

Tao Shi

Ohio State University (OSU)

Blankenship Hall-2010
901 Woody Hayes Drive
Columbus, OH OH 43210
United States

Hansheng Wang (Contact Author)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

HOME PAGE: http://hansheng.gsm.pku.edu.cn

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