Emotion recognition from blog articles

Suicide of college students has been a universal phenomenon in the world. And the phenomenon has become more and more sever because of the complex and drastic competitions. With the popularization of Internet and the development of information processing technologies, a lot of people have established their own blog Websites to write down their experiences and express their feelings at times. It will be very helpful if the computer can recognize the emotions expressed in blog pages automatically. And then it will be convenient for teachers or psychological consultants to monitor the affective information of college students and take measures for the depression prevention when necessary. Owing to the advances in affective computing and natural language processing, researches have begun to pay more attention to the emotion recognition in NLP all over the world. This paper outlines the approach we have developed to construct a blog emotion-recognizing system. It is based on the lexical contents of words and structural characteristics of blog articles. For the emotion computing of articles, two methods are proposed and the experimental results are compared and analyzed. Finally, the implications of the results are discussed for the future's direction of the research.