With　the　rapid　development　of　mobile　SMS　(short　message　service),　spam　messages　have　grown　explosively　which　trouble　our　daily　lives　seriously　and　lead　to　the　loss　of　telecom　operators.　In　this　paper,　an　online　spam　filter　based　on　the　analysis　of　two　criteria　of　content　representations　and　relationship　between　the　senders　and　receivers　in　social　network　is　proposed.　A　Naïve　Bayesian　classifier　is　used　to　build　up　the　filter　including　both　the　content　features　and　social　network　features.　We　use　the　data　provided　by　a　partner　telecom　operator　to　do　the　experiments.　The　results　show　that　our　model　is　effective　and　satisfies　all　the　requirements　of　our　partner　and　will　be　deployed　recently.　©　2012　IEEE.