According to the investigation report of the Department of Health, Executive Yuan, R.O.C. in 2007, it is estimated that about 7.3% of Taiwan's population suffer from the major depressive disorder. How to identify patients with depression tendency is one of important health issues. Thus, this project tries to develop a novel technique to automatically identify the depression tendency of bloggers using their blog posts. With the fast growth of social networks, bloggers usually write daily posts with their emotion and events happened in work, home, or life. Although there are lots of research works about emotion analysis and classification, to our knowledge, there is no work focusing on prediction of blogger's depression tendency based on emotion analysis. In this project, we try to analyze key factors affecting major depressive disorder, such as negative event, negative emotion, symptom and negative thought, and then use these four factors to assist bloggers to predict depression tendency. Therefore, we focus on the investigation of the following two research issues (1) analysis of relevant factors of depression on blog posts written by patients with the major depressive disorder, (2) development of event-emotion-driven depression tendency prediction model.