Making sentiment analysis algorithms scalable

In this paper we introduce a simplied approach to sentiment analysis: a lexicon-driven method based upon only adjectives and adverbs. This method is compared in cross-validation with other known techniques and then compared directly to the gold standard, a sample of human subjects asked to deliver the same class of judgments computed by the method. We prove that the method is similar in accuracy and precision with the other methods. We nally argue that the approach we employ is more valid than others for it is scalable, and exportable to languages other than English.