Main Article Content
This paper focuses on the construction of models, through automatic learning, for sentimental analysis, which allow to obtain the polarity of a tweet by taking advantage of the information obtained through an information retrieval process. For this purpose, the features derived from the classification generated by such a system in response to the consultation of the document to be analyzed will be used. Through this combination of tools we will achieve a language-independent sentiment analysis, reaching accuracies comparable to other state-of-the art approaches but at a much higher speed.
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