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Classification of controversial news article based on disputant relation by SVM classifier

机译:基于SVM分类器的争议关系的争议新闻文章分类

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The controversial news issues grab much attention from the public. But it is difficult to understand completely the issue for a normal reader. “Disputant relation based method” classifies the opposing views of the news which can help readers to understand the issues easily. Generally for classifying news articles Disputant relation based method is used. We study disputant relation based method and using its concept classify the news issues. It is known that the participants (disputants) of a controversy are the important feature for understanding the conversation. The disputant relation based method performs unsupervised SVM classification. In this paper we perform both supervised & unsupervised SVM classification for understanding disputant relation based method more closely through the “opponent based frame”. Ultimately we analyze & compare both classifications results. Disputant relation based method consist of three stages: Disputant mining, Disputant partitioning and article classification.
机译:有争议的新闻问题从公众抓住了很多关注。但很难完全理解正常读者的问题。 “基于争议关系的方法”对该消息的反对视图进行分类,这可以帮助读者轻松理解问题。一般来说,对于基于新闻文章的争论文章,使用了基于争议关系的方法。我们研究基于争议的方法和使用其概念对新闻问题进行分类。众所周知,争议的参与者(争议者)是理解谈话的重要特征。基于争议性关系的方法执行无监督的SVM分类。在本文中,我们通过“基于对手的框架”更密切地关注基于争议性关系的方法的监督和无监督的SVM分类。最终,我们分析并比较两个分类结果。基于争议的关系的方法包括三个阶段:争议挖掘,争议分区和文章分类。

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