Sentiment Analysis on the People's Daily

We propose a semi-supervised bootstrap-ping algorithm for analyzing China’s for-eign relations from the People’s Daily. Our approach addresses sentiment tar-get clustering, subjective lexicons extrac-tion and sentiment prediction in a unified framework. Different from existing algo-rithms in the literature, time information is considered in our algorithm through a hierarchical bayesian model to guide the bootstrapping approach. We are hopeful that our approach can facilitate quantita-tive political analysis conducted by social scientists and politicians. 1