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).　©　2017　IEEE.