Abstract
In this work, we present a method for classifying the quality of blog comments using Linear-Chain Conditional Random Fields (CRFs). This approach is found to yield high accuracy on binary classification of high-quality comments, with conversational features contributing strongly to the accuracy. We also present a new corpus of blog data in conversational form, complete with user-generated quality moderation labels from the science and technology news blog Slashdot.
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FitzGerald, N., Carenini, G., Murray, G., Joty, S. (2011). Exploiting Conversational Features to Detect High-Quality Blog Comments. In: Butz, C., Lingras, P. (eds) Advances in Artificial Intelligence. Canadian AI 2011. Lecture Notes in Computer Science(), vol 6657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21043-3_15
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DOI: https://doi.org/10.1007/978-3-642-21043-3_15
Publisher Name: Springer, Berlin, Heidelberg
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