Paper: Modeling Mutual Influence Between Social Actions and Social Ties

ACL ID C14-1081
Title Modeling Mutual Influence Between Social Actions and Social Ties
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

In online social media, social action prediction and social tie discovery are two fundamental tasks for social network analysis. Traditionally, they were considered as separate tasks and solved inde- pendently. In this paper, we investigate the high correlation and mutual influence between social actions (i.e. user-behavior interactions) and social ties (i.e. user-user connections). We propose a unified coherent framework, namely mutual latent random graphs (MLRGs), to flexibly encode evidences from both social actions and social ties. We introduce latent, or hidden factors and coupled models with users, users? behaviors and users? relations to exploit mutual influence and mutual benefits between social actions and social ties. We propose a gradient based optimization algorithm to efficien...