Compressing and mining social network data
Connor C.J. Hryhoruk, Carson K. Leung
Abstract
Nowadays, social networking is popular. As such, numerous social networking sites (e.g., Facebook, YouTube, Instagram) are generating very large volumes of social data rapidly. Valuable knowledge and information is embedded into these big social data. As the social network can be very sparse, it is awaiting to be (a) compressed via social network data compression and (b) analyzed and mined via social network analysis and mining. We present in this paper a solution for compressing and mining social networks. It gives an interpretable compressed representation of sparse social network, and discovers interesting patterns from the social network. Results of our evaluation show the effectiveness of our solution in explaining the compression and mining of the sparse social network data.