Title of article
Automatic categorisation of comments in social news websites
Author/Authors
Santos، نويسنده , , Igor and de-la-Peٌa-Sordo، نويسنده , , Jorge and Pastor-Lَpez، نويسنده , , Iker and Galلn-Garcيa، نويسنده , , Patxi and Bringas، نويسنده , , Pablo G.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2012
Pages
9
From page
13417
To page
13425
Abstract
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.
Keywords
Spam detection , information filtering , Machine-learning , Web categorisation , Content filtering
Journal title
Expert Systems with Applications
Serial Year
2012
Journal title
Expert Systems with Applications
Record number
2352829
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