A comparative study of blog comments spam filtering with machine learning techniques

Abstract

In this paper we compare four machine learning techniques for spam filtering in blog comments. The machine learning techniques are: Naïve Bayes, K-nearest neighbors, neural networks and support vector machines. In this work we used a corpus of 1021 blog comments with 67% spam, the results of the filtering using 10 fold cross-validation are presented. © 2010 Springer-Verlag Berlin Heidelberg.