We describe a supervised system that uses optimized Conditional 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.
CITATION STYLE
Onyibe, C. J., & Habash, N. (2017). OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 670–674). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s17-2111
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