Key nodes mining for complex networks based on local gravity model

Abstract

Identification of key nodes in complex networks can effectively speed up the spread of favourable information or prevent the spread of rumours and diseases. An algorithm based on local gravity model is proposed to mine the key spreaders in complex networks. The existing algorithms based on gravity model consider the shortest distance between nodes. However, nodes not only influence each other through the shortest path, which will lead the loss of information between nodes. Different from the existing gravity model, the distance considered in this model is not the shortest distance between nodes, but the reciprocal of the number of feasible paths between nodes. Conveniently, the model is called FPLGM (Local Gravity Model Based on Feasible Paths). Ten different networks are utilised to verify the effectiveness of FPLGM. Results show that the FPLGM performs best in comparison with the well-known state-of-the-art methods.