Abstract：Weblog is an important media for people to express their personal opinions and sentiment, which generally involve several topics or implied public opinions. The existing sentiment analysis researches on these user generation content are mostly in document level instead of fine granalarities. This paper proposes a novel method based on LDA topic model and HowNet lexicon to determine the sentiment orientation of blogs with multi-aspect topics. The new method utilizes data corpus to train the LDA topic model at first. Then it identifies and segments topics with the trained topic model, which taking a slide window as the basic processing unit. After that, the topics of paragraphs can be identified. And then the method conducts the sentiment analysis on topic paragraphs with HowNet lexicon. The new method can help to simultaneous identify multi-aspect topics and the sentiment orientation of these topics. The experiment results show that this approach can not only obtain a good topic partitioning results, but also help to improve sentiment analysis accuracy. Key wordsmulti-aspect sentiment analysis; blog sentiment analysis; LDA topic model; HowNet lexicon
2013, Vol. 27 
