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


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)
Number of pages5
StatePublished - Aug 1 2017

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