Negative　life　event　is　an　important　reason　of　causing　depression,　such　as　the　death　of　family　members,　quarreled　with　the　spouse,　fired　by　the　boss　or　blamed　by　the　teacher.　The　combination　of　a　subject　and　a　negative　life　event　is　called　a　language　pattern　of　negative　life　events.　Therefore,　whether　it　can　understand　those　web　texts　with　depression　trend　by　identifying　these　negative　life　event　language　patterns　automatically　and　accurately,　which　is　important　to　establish　effective　and　practical　psychiatric　network　services.　Such　as　the　question　(parent:　divorce::　boyfriend:?),　this　study　applied　the　distributional　word　embeddings　to　mine　the　language　patterns　of　negative　life　events.　The　experimental　results　showed　that　the　MRR　index　reached　0.71.　©　The　Association　for　Computational　Linguistics　and　Chinese　Language　Processing