A Two-Stage Classifier for Sentiment Analysis
Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham · 2013
In this paper, we present a study applying re-ject option to build a two-stage sentiment po-larity classification system. We construct a Naive Bayes classifier at the first stage and a Support Vector Machine at the second stage, in which documents rejected at the first stage are forwarded to be classified at the second stage. The obtained accuracies are comparable to other state-of-the-art results. Furthermore, experiments show that our classifier requires less training data while still maintaining rea-sonable classification accuracy. 1