String Kernels for Polarity Classification: A Study Across Different Languages
The polarity classification task has as objective to automatically deciding whether a subjective text is positive or negative. Using a cross-domain setting implies the use of different domains for the training and testing. Recently, string kernels, a method which does not employ domain adaptation techniques has been proposed. In this work, we analyse the performance of this method across four different languages: English, German, French and Japanese. Experimental results show the strong potential of this approach independently from the language.
KeywordsString kernels Sentiment analysis Single-domain Cross-domain
The work of the third author was partially funded by the Spanish MINECO under the research project SomEMBED (TIN2015-71147-C2-1-P).
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