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Aspect Summarization from Blogsphere for Social Study

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2 Author(s)

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. Keywords: weblogs, social study, opinion extraction, reason summarization, text mining, sentiment classicization

Published in:

Data Mining Workshops, 2007. ICDM Workshops 2007. Seventh IEEE International Conference on

Date of Conference:

28-31 Oct. 2007

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