Emotion recognition on text has wide applications. In this study, we make an analysis on sentence emotion based on emotion words using Ren-CECps (a Chinese emotion corpus). Some classification methods (including C4.5 decision tree, SVM, NaiveBayes, ZEROR, and DecisionTable) have been compared. Then a supervised machine learning method (Polynomial kernel method) is proposed to recognize the eight basic emotions (Expect, Joy, Love, Surprise, Anxiety, Sorrow, Angry and Hate). Using Ren-CECps, we get the emotion lexicons for the eight basic emotions. Polynomial kernel (PK) method is used to compute the similarities between sentences and the eight emotion lexicons. Then the experiential knowledge derived from Ren-CECps is used to recognize whether the eight emotion categories are present in a sentence. The experiments showed promising results.