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This paper defines a systematic approach to Opinion Mining (OM) on YouTube comments by (i) modeling classifiers for predicting the opinion polarity and the type of comment and (ii) proposing ro-bust shallow syntactic structures for im-proving model adaptability. We rely on the tree kernel technology to automatically ex-tract and learn features with better gener-alization power than bag-of-words. An ex-tensive empirical evaluation on our manu-ally annotated YouTube comments corpus shows a high classification accuracy and highlights the benefits of structural mod-els in a cross-domain setting. 1
Severyn et al. (2014) studied this question.