Online　social　networks　have　gradually　permeated　into　every　aspect　of　people＇s　life.　As　a　research　hotspot　in　social　network,　user　influence　is　of　theoretical　and　practical　significant　for　information　transmission,　optimization　and　integration.　A　prominent　application　is　a　viral　marketing　campaign　which　aims　to　use　a　small　number　of　targeted　influence　users　to　initiate　cascades　of　influence　that　create　a　global　increase　in　product　adoption.　In　this　paper,　we　analyze　mainly　evaluation　methods　of　user　influence　based　on　IDM　evaluation　model,　PageRank　evaluation　model,　use　behavior　model　and　some　other　popular　influence　evaluation　models　in　currently　social　network.　And　then,　we　extract　the　core　idea　of　these　models　to　build　our　influence　evaluation　model　from　two　aspects,　relationship　and　activity.　Finally,　the　proposed　approach　was　validated　on　real　world　datasets,　and　the　result　of　experiments　shows　that　our　method　is　both　effective　and　stable.