Aspect Summarization from Blogsphere for Social Study

In this paper, we study the problem of summarizing reasons from blogsphere for social study. We regard weblogs as a source for collecting non-discrete public opinions, where genuine reasons/aspects can be found. To extract the reason inside the blogs, we define four tasks: irrelevant blog filtering, reason/non-reason classification, polarity identification, and reason summarization. We solve the reason/non-reason classification problem by selecting a set of topic related words and brief the reasons by clustering paragraphs containing aspects after sentiment classification. Initial experiments on two topics show an encouraging result on the proposed framework.

• Type: Conference
• Year: 2007
• Where: ICDM
• Authors: Chia-Hui Chang, Kun-Chang Tsai
• Keywords: Data Mining, ICDM 2007, Non-discrete Public Opinions, Reason/non-reason Classification, Reason/non-reason Classification Problem