Visual　words　description　method　has　been　widely　applied　in　the　fields　of　social　image＇s　tag　ranking,　tag　recommendation　and　annotation.　At　present,　visual　words　are　usually　obtained　by　unsupervised　clustering　methods　which　lead　to　generate　many　unnecessary　and　non-descriptive　words.　Therefore,　how　to　make　visual　words　be　descriptive　has　become　a　very　meaningful　task　for　tag　ranking　of　social　image.　However,　for　compressed　social　image　on　the　network,　visual　words　are　created　after　fully　decompressing　a　compressed　image　into　pixel　domain.　In　this　paper,　creating　descriptive　visual　words　in　compressed　domain　is　proposed　for　tag　ranking　of　compressed　social　image.　Firstly,　the　traditional　visual　words　are　created　by　using　the　partly　decoded　data;　then　the　descriptive　visual　words　are　selected　from　traditional　visual　words　by　the　VisualWordRank　ranking　algorithm;　finally　the　descriptive　visual　words　are　applied　to　rank　the　tag　of　social　image.　Experimental　results　show　the　descriptive　visual　words　can　improve　the　accuracy　of　tag　ranking,　which　further　prove　our　method　has　more　descriptive　ability.　Besides　that,　our　method　also　reduces　the　processing　time　for　compressed　social　image　greatly.　©　2015　IEEE.