OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields

Chukwuyem Onyibe, Nizar Habash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe a supervised system that uses optimized Condition Random Fields and lexical features to predict the sentiment of a tweet. The system was submitted to the English version of all subtasks in SemEval-2017 Task 4.
Original languageUndefined
Title of host publicationProceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Place of PublicationVancouver, Canada
PublisherAssociation for Computational Linguistics (ACL)
Pages670-674
Number of pages5
DOIs
StatePublished - Aug 1 2017

Cite this

Onyibe, C., & Habash, N. (2017). OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) (pp. 670-674). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/S17-2111