The　research　of　topic　popularity　prediction　problem　can　be　an　important　significance　for　maximizing　the　propagation　effects　of　network　advertisements　as　well　as　guiding　and　controlling　the　network　consensus.　Firstly,　according　to　user　relationship　and　topic　factor,　user　influence　is　computed　and　topic　influence　is　defined.　Then,　based　on　aging　theory,　topic　energy　value　is　calculated　by　considering　both　topic　influence　and　the　number　of　microblogs　related　to　the　topic,　and　the　heat　of　topic　is　quantified.　Finally,　an　method　named　topic　popularity　prediction　of　microblog　based　on　wavelet　transformation　and　autoregressive　integrated　moving　average　model　is　proposed　to　predict　topic　popularity　of　microblog　and　forecast　when　a　topic　will　hit　the　peak.　Experimental　results　show　that　the　proposed　method　can　effectively　predict　the　topic　popularity　and　the　peak　of　a　topic　with　lower　residual　error　and　omission　rate.　©,　2015,　Journal　of　Pattern　Recognition　and　Artificial　Intelligence.　All　right　reserved.