Currently one of core issues of link prediction is how to rationally and efficiently combine link attributes, node attributes and other relevant information for forecasting purposes. Aim at this problem, we propose a link prediction algorithm based on influence and interest, which mainly consists of quantizing the influence of nodes by topology structure information and simulating users' interests by text information. These two types of information are aggregated to give the relation score to the node pairs. High-scoring pair of nodes which represents a strong link. Experiments on real datasets show the method proposed in this paper is feasible.