Chinese Short Text Semanteme analysis and Emotion value Quantization Algorithm

摘要

With the development of social platform, the number of status people use to express their feelings is so large that the requirement for analyzing emotion value and emotion trend quantitatively is so hot. To meet this need, we propose a FSM based model aiming at the feature of short text in Chinese. And with it, we can then evaluate the emotion value in a scientific and quantitative way. Through experiments, we prove the accuracy and the efficiency of this model.