A Hybrid Approach for Recovering Information Propagational Direction

With the rapid development of network technology, people are communicating with each other through a variety of network access, such as computer, mobile phone, tablet, etc., for the sharing of information and interactive behavior. The flow of information is directional, but this directionality is usually hidden. In recent years, link prediction technology has been developed very rapidly in social network analysis. The active and passive of the relationship, in social network, could be identified via undirected relationship network structure. However, this approach only focuses on the topological structure while ignoring the information shared between individuals, which is not suitable for study in terms of information propagation. To solve this problem, we propose a hybrid approach termed DRHM to recover the information sharing direction in networks. It combines not only topology structure but also node content. Since the algorithm is based on edge structure, it is equally applicable to large-scale data set. The experiment has demonstrated that our algorithm performs well in information propagational network.