Discoverying　hidden　communities　in　various　kinds　of　complicated　networks　is　a　considerable　research　direction　in　the　field　of　complex　network　analysis.　Its　goal　is　to　discover　the　structures　of　communities　in　complex　networks.　The　algorithms　devised　upon　the　Attractor　dynamic　distance　mechanism　are　capable　of　finding　stable　communities　with　various　sizes.　However,　they　still　have　deficiencies　in　overlapping　community　discovery　and　runtime　efficiency.　An　overlapping　community　discovery　algorithm　based　on　triangle　coarsening　and　dynamic　distance　is　posed　in　this　paper.　First,　a　coarsening　strategy　devised　upon　triangle　is　adopted　to　reduce　networks’　sizes.　Second,　for　the　coarsened　networks,　a　dynamic　distance　processing　mechanism　based　on　overlapping　Attractors　is　used　to　discover　the　overlapping　communities　in　the　networks.　Finally,　the　communities　in　the　raw　networks　are　obtained　through　anti-roughening　steps.　The　experiments　on　different　datasets　demonstrate　that　the　proposed　algorithm　not　only　can　discover　the　overlapping　communities　accurately　but　also　has　low　time　complexity.　©　Springer　Nature　Singapore　Pte　Ltd.　2019.