Although　they　have　small-world　and　searchable　characteristics,　social　networks　always　protect　local　structure　which　makes　local　search　very　hard.　Social　networks　not　only　have　power-law　distribution,　but　also　have　higher　connectivity　or　clustering　characteristics.　Meanwhile,　several　social　networks　are　weighted　and　directed.　Hence　we　should　utilize　these　extra　information.　In　this　paper,　we　propose　and　theoretically　analyze　local　search　strategies　such　as　SS,　O1,　O2,　SPD　and　LPD　which　consider　weights,　single　link　characteristics　and　direction　information.　We　finally　demonstrate　the　results　of　these　strategies　on　Enron　Email　networks.　Experimental　results　show　that　weighted　and　directed　information　is　able　to　enhance　the　efficiency　of　local　search.