Abstract: Social media networks include not only multi-modal data,such as users,text,images,video,and so on,but also collective effect between data of different modals.In order to better describe social media networks and provide better services for applications,this paper proposed a deep neural network based social media network model.The proposed model models data of each single modal with a deep neural network,and then gets a latent feature representation for each modal data.For data between two different modals,a Gaussian distributed prior matrix and two posterior distributions of different modals were applied to build a generative model that describes the collective effect between two diffe-rent modals.The experiments show that the proposed model has better prediction performance in link analysis of networks than related works,and can describe the whole underlying social media network effectively.

Key words: Deep learning,Neural networks,Social media network,Feature learning,Link prediction