A Joint Topic Viewpoint Model for Contention Analysis
نویسندگان
چکیده
This work suggests a fine-grained mining of different types of contentious documents, towards a summarization of contention issues. We propose a Joint Topic Viewpoint model (JTV) for the unsupervised identification and the clustering of arguing expressions according to the latent topics they discuss and the implicit viewpoints they voice. A set of experiments is conducted on three type of contentious documents: a survey, online debates and editorials. Qualitative and quantitative evaluations of the model’s output are performed in context of different contention issues. Analysis of experimental results shows the effectiveness of the proposed model to automatically and accurately detect recurrent patterns of arguing expressions.
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تاریخ انتشار 2014