In this paper, aiming to automatically distinguish subjective words from objective ones in Chinese, the study performs a subjectivity ranking test on Chinese adjectives and verbs. The paper exploits subjectivity clues and the subjectivity of Chinese characters. The subjectivity clues are further divided into gradability clues and subject clues. The study then uses graph-based algorithms to calculate the subjectivity originated from subjectivity clues. The subject clues and subjectivity of Chinese characters are novel ideas in such tasks. Five annotators are asked to label subjectivity of 500 words, from which the gold standard is built upon and evaluates rankings in various settings. It is shown that when words to be ranked occur frequently, this approach can outperform or match some human annotators. Furthermore, although the study only an unlabeled corpus, more prior knowledge can be incorporated into the graph-based approach.