Automatic categorisation of comments in social news websites
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摘要
The use of the social web has brought a series of changes in the way how content is created. In particular, social news sites link stories and the different users can comment them. In this paper, we propose a new method based on different features extracted from the text able to categorise the comments. To this end, we use a combination of statistical, syntactic and opinion features and machine-learning classifiers to classify a comment within three different categorisation types: the focus of the comment, the type of information contained in the comment and the controversy level of the comment. We validate our approach with data from ‘Menéame’, a popular Spanish social news site.
论文关键词:Spam detection,Information filtering,Content filtering,Machine-learning,Web categorisation
论文评审过程:Available online 7 June 2012.
论文官网地址:https://doi.org/10.1016/j.eswa.2012.05.061