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2010
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A Comparison of Stylometric and Lexical Features for Web Genre Classification and Emotion Classification in Blogs

9 years 11 months ago
A Comparison of Stylometric and Lexical Features for Web Genre Classification and Emotion Classification in Blogs
In the blogosphere, the amount of digital content is expanding and for search engines, new challenges have been imposed. Due to the changing information need, automatic methods are needed to support blog search users to filter information by different facets. In our work, we aim to support blog search with genre and facet information. Since we focus on the news genre, our approach is to classify blogs into news versus rest. Also, we assess the emotionality facet in news related blogs to enable users to identify people's feelings towards specific events. Our approach is to evaluate the performance of text classifiers with lexical and stylometric features to determine the best performing combination for our tasks. Our experiments on a subset of the TREC Blogs08 dataset reveal that classifiers trained on lexical features perform consistently better than classifiers trained on the best stylometric features. Keywords-Document Classification; Data Mining; Features
Elisabeth Lex, Andreas Juffinger, Michael Granitze
Added 22 Mar 2011
Updated 22 Mar 2011
Type Journal
Year 2010
Where DEXAW
Authors Elisabeth Lex, Andreas Juffinger, Michael Granitzer
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