• 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