Emotional feature extraction is an important step in text sentiment classification, so choosing emotional feature correctly and giving a reasonable sentiment weight are the premise to guarantee classification precision. A Chinese text emotional feature extraction algorithm is proposed based on multiple lexicons including basic semantic lexicon, conjunction lexicon and word distance. The experiment results show that the algorithm outperforms some classic feature extraction algorithms of HM, SO-PMI and word semantic distance etc.