Abstract
As the popularity of weblogging continues to grow, the automatic quality assessment of user generated content shifts more and more into the focus of scientific and commercial discussions. This paper examines Web Mining and machine learning methods for these purposes. Based on automatically detectable features, various blog-specific quality models are trained using machine learning methods. Data from several thousand blogs in three languages has been collected. Along with the assessment of their efficiency, the most useful attributes are identified. Thus, this work points at the characteristics of high-quality blogs and develops basic ideas for their automatic analysis.
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Hellmann, R., Griesbaum, J., Mandl, T. (2010). Quality in Blogs: How to Find the Best User Generated Content. In: Abramowicz, W., Tolksdorf, R. (eds) Business Information Systems. BIS 2010. Lecture Notes in Business Information Processing, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12814-1_5
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DOI: https://doi.org/10.1007/978-3-642-12814-1_5
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