Structural analysis in multi-relational social networks

• Main Authors: DAI, Bingtian, CHUA, Freddy, LIM, Ee Peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1541; https://ink.library.smu.edu.sg/context/sis_research/article/2540/viewcontent/Structural_Analysis_in_Multi_Relational_Social_Networks.pdf
• Institution: Singapore Management University

Modern social networks often consist of multiple relations among individuals. Understanding the structure of such multi-relational network is essential. In sociology, one way of structural analysis is to identify different positions and roles using blockmodels. In this paper, we generalize stochastic blockmodels to Generalized Stochastic Blockmodels (GSBM) for performing positional and role analysis on multi-relational networks. Our GSBM generalizes many different kinds of Multivariate Probability Distribution Function (MVPDF) to model different kinds of multirelational networks. In particular, we propose to use multivariate Poisson distribution for multi-relational social networks.