Existing　models　for　measuring　user　social　influence　fail　to　integrate　both　opinion　and　topic　information.　Therefore,　a　new　constrained　nonnegative　tensor　factorization　method　combining　user＇s　opinion　and　the　topical　relevance　was　proposed.　The　method　represented　user＇s　comment　relations　as　3-order　tensor,　factorized　the　comments　tensor　constrained　by　Laplacian　topical　matrix,　and　then　measures　user　influence　according　to　the　latent　factors　resulting　from　the　tensor　factorization.　Thus,　the　new　method　not　only　was　capable　to　effectively　calculate　the　strength　of　user　social　influence　on　given　topic,　but　also　kept　the　polarity　allocation　of　social　influence.　The　experimental　result　shows　that　the　performance　of　the　proposed　method　is　better　than　that　of　the　baseline　methods　such　as　OOLAM,　TwitterRank,　etc.　©　2016,　Editorial　Board　of　Journal　on　Communications.　All　right　reserved.