Mobile　opportunistic　networks　make　use　of　a　new　networking　paradigm　that　takes　advantage　of　node　mobility　to　distribute　information.　Studying　their　inherent　properties　of　information　dissemination　can　provide　a　straightforward　explanation　on　the　potentials　of　mobile　opportunistic　networks　to　support　emerging　applications　such　as　mobile　commerce,　emergency　services,　and　so　on.　In　this　paper,　we　investigate　the　inherent　properties　of　information　dissemination　using　the　Levy　mobility　model　to　characterize　the　movement　pattern　of　the　nodes.　Because　Levy　mobility　can　closely　mimic　human　walk,　the　analysis　model　we　adopt　is　practical.　Our　analyses　are　taken　from　the　perspectives　of　small-and　large-scales.　From　the　perspective　of　small-scale,　the　distribution　of　the　minimum　time　needed　by　the　information　to　spread　to　a　given　region　is　investigated;　from　the　perspective　of　large-scale,　the　bounds　of　the　probability　of　the　earliest　time　at　which　the　information　arrives　in　a　region　that　is　sufficiently　farther　away　are　obtained.　We　also　provide　the　rate　that　such　probability　approaches　zero　as　the　distance　to　the　region　increases　to　infinity.　Finally,　our　main　results　are　validated　by　the　numerical　simulations.