At　present,　the　network　pyramid　scheme　has　become　a　major　tumor　that　hinders　social　development.　In　order　to　curb　the　propagation　of　the　network　pyramid　scheme　and　effectively　identify　the　pyramid　scheme　text　in　the　network,　this　study　proposes　a　joint　topic　model,　Paragraph　Vector　Latent　Dirichlet　Allocation　(PV_LDA),　based　on　the　characteristics　of　high-yield,　high　rebate,　hierarchical　salary　and　text　topic　diversity　described　in　the　text.　The　model　uses　the　paragraph　as　the　minimum　processing　unit　to　generate　the　topic　distribution　matrix　of　＂high-interest　rate＂　and　＂hierarchical　salary＂　from　the　network　pyramid　scheme　text.　The　Gibbs　sampling　is　used　to　derive　the　＂pyramid　scheme＂　topic　distribution　matrix　represented　by　the　two　features,　which　is　used　for　classification　processing　by　the　classifier.　the　classification　accuracy　rate　for　the　network　pyramid　scheme　text　can　reach　86.25%.　The　conclusions　show　that　the　topic　model　proposed　in　this　paper　can　capture　the　characteristics　of　the　pyramid　scheme　more　reasonably.