A two-stage classifier for sentiment analysis

Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)


In this paper, we present a study applying reject option to build a two-stage sentiment polarity 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 reasonable classification accuracy.
Original languageEnglish
Title of host publicationProceedings of the 6th International Joint Conference on Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Number of pages5
Publication statusPublished - 2013
Externally publishedYes
EventInternational Joint Conference on Natural Language Processing (6th : 2013) - Nagoya, Japan
Duration: 14 Oct 201318 Oct 2013


ConferenceInternational Joint Conference on Natural Language Processing (6th : 2013)
CityNagoya, Japan


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