Publication Type
Conference Paper
Version
submittedVersion
Publication Date
2012
Abstract
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.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
SIAM International Conference on Data Mining (SDM2012)
City or Country
Anaheim, California
Citation
DAI, Bingtian; CHUA, Freddy; and LIM, Ee Peng.
Structural analysis in multi-relational social networks. (2012). SIAM International Conference on Data Mining (SDM2012).
Available at: https://ink.library.smu.edu.sg/sis_research/1541
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www.siam.org/meetings/sdm12/sdm12_abstracts.pdf
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons