To　detect　network　event　efficiently　in　the　large　scaled　and　heterogeneous　network　environment,　this　research　puts　forward　a　new　approach　based　on　time-slice　and　multi　metadata　fusion　for　Multimedia　Social　Event　Detection.　Firstly,　a　user-time　model　by　time-slicing　with　user　information　was　constructed　to　reduce　the　scale　of　data.　Secondly,　the　multi　metadata　fusion　method　and　density-based　clustering　(DBSCAN)　algorithm　were　applied　to　detect　social　events.　The　comparison　experiments　of　the　latest　dataset-SED2014　indicate　that　the　new　approach　is　faster　and　more　accurate　to　detect　the　network　social　event　compared　with　the　existing　methods.　©,　2015,　Beijing　University　of　Technology.　All　right　reserved.