Opinion　mining　on　regular　documents　like　movie　reviews　and　product　reviews　has　been　intensively　studied.　In　this　paper　we　focus　on　opinion　mining　on　short　e-commerce　feedback　comments.We　aim　to　compute　a　comprehensive　rating　profile　for　sellers　comprising　of　dimension　ratings　and　weights.　We　propose　an　algorithm　to　mine　feedback　comments　for　dimension　ratings,　combining　opinion　mining　and　dependency　relation　analysis,　a　recent　development　in　natural　language　processing.　We　formulate　the　problem　of　computing　dimension　weights　from　ratings　as　a　factor　analytic　problem　and　propose　an　effective　solution　based　on　matrix　factorisation.　Extensive　experiments　on　eBay　and　Amazon　data　demonstrate　that　our　proposed　algorithms　can　achieve　accuracies　of　93.1%　and　89.64%　respectively　for　identifying　dimensions　and　ratings　in　feedback　comments,　and　the　weights　computed　can　accurately　reflect　the　amount　of　feedback　for　dimensions.　©　Springer-Verlag　2013.