Mining　opinion　targets　and　opinion　words　is　a　fundamental　task　for　the　Chinese　online　media　to　mine　opinion　and　analyze　sentiment.　The　key　to　enhancing　the　effectiveness　of　opinion　target　and　opinion　word　is　to　integrate　syntactic　relations　and　co-occurrence　relations　between　opinion　target　and　opinion　word　into　the　mining　model.　A　novel　approach　based　on　a　multi-layer　relation　graph　model　is　proposed　to　extract　opinion　targets　and　opinion　words　from　Chinese　social　media.　First,　the　word　alignment　model　is　employed　to　extract　the　candidates　of　opinion　target　and　opinion　word　candidates.　Second,　a　multi-layer　relation　graph　is　constructed　by　the　syntactic　inter-relations　between　opinion　target　and　opinion　word,　the　co-occurrence　intra-relations　among　opinion　targets,　and　the　co-occurrence　intra-relations　among　opinion　words.　Third,　a　random-walk　algorithm　is　adopted　to　calculate　the　confidence　of　each　opinion　target　candidate　and　opinion　word　candidate.　Finally,　opinion　targets　and　opinion　words　are　extracted　according　to　their　confidence　values.　Experimental　results　show　that　the　presented　method　can　not　only　achieve　significant　improvement　over　previous　methods,　but　also　have　good　robustness.　Copyright　©　2017　Acta　Automatica　Sinica.　All　rights　reserved.