Abstract: In the real world, the structure of social networks is not static, but varying with times changing, and the same communities as an essential feature of social networks is also true. An incremental dynamic community detecting algorithm is proposed to reveal the actual communities based attribute weighted networks. It associates attribute information with topology graph and defines topological potential attraction between nodes and communities, using the incremental comparing with previous time to update the current community structure. The experiment on real network data proved that the proposed algorithm could be more effectively and timely to discover meaningful community structure, and having a smaller time complexity.