The research aimes at opinion sentence identification and element extraction in sentiment analysis in Chinese micro blogs. In the aspect of opinion sentence identification, the authors propose a new algorithm to compute the micro blog semantic sentiment orientation using sentiment words and emotional impact factors. In element extraction, subject term classification and the association rule are applied, accompanied with a series of pruning, sifting and delimiting rules to extract evaluative objects in micro blogs. Through mutual filtering of opinion sentence identification and element extraction, the recall rate is improved further. The released data of the sixth Chinese opinion analysis evaluation is adopted as experimental data. The results show that the methods perform well in opinion sentence recognition and element extraction. The precision ratio, recall rate, and F -value of opinion sentence identification are 95.62%,54.10% and 69.10%, respectively. The precision ratio, recall rate, and F-value of element extraction are22.07%, 12.66% and 16.09%, respectively.