With　the　extensive　development　of　big　data　and　social　networks,　the　user　profile　field　has　received　much　attention.　User　profiling　is　essential　for　understanding　the　characteristics　of　various　users,　contributing　to　better　understanding　of　their　requirements　in　specific　scenarios.　User-generated　contents　which　directly　reflect　people＇s　thoughts　and　intention　are　a　valuable　source　for　profiling　users,　among　which　user　reviews　by　nature　are　invaluable　sources　for　acquiring　user　requirements　and　have　drawn　increasing　attention　from　both　academia　and　industry.　However,　review-based　user　profiling　(RBUP),　as　an　emerging　research　direction,　has　not　been　systematically　reviewed,　hindering　researchers　from　further　investigation.　In　this　work,　we　carry　out　a　systematic　mapping　study　on　review-based　user　profiling,　with　an　emphasis　on　investigating　the　generic　analysis　process　of　RBUP　and　identifying　potential　research　directions.　Specifically,　51　out　of　2478　papers　were　carefully　selected　for　investigation　under　a　standardized　and　systematic　procedure.　By　carrying　out　in-depth　analysis　over　such　papers,　we　have　identified　a　generic　process　that　should　be　followed　to　perform　review-based　user　profiling.　In　addition,　we　perform　multi-dimensional　analysis　on　each　step　of　the　process　in　order　to　review　current　research　progress　and　identify　challenges　and　potential　research　directions.　The　results　show　that　although　traditional　methods　have　been　continuously　improved,　they　are　not　sufficient　to　unleash　the　full　potential　of　large-scale　user　reviews,　especially　the　use　of　heterogeneous　data　for　multi-dimensional　user　profiling.