One of the traditional ways for detecting dynamic communities is to find the communities at each interval through the static community detection algorithms. However, it usually leads to high computation complexity. In this paper, a novel algorithm based on the MapReduce model and the label propagation progress with the strategy of incremental related vertices is proposed, which is called PLPIRV (Parallel Label Propagation and Incremental Related Vertices). Based on the communities found at the previous interval, the new algorithm adjusts the communities the incremental related vertices belong to. The clustering of the whole network can be avoided by incrementally analyzing the variation of the networks, so that the time cost can be greatly reduced. Experiments on artificial and real datasets show that the proposed algorithm performs well on dynamic community detection. (Abstract).