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

Chukwuyem Onyibe; Nizar Habash

doi:10.18653/v1/S17-2111

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

Chukwuyem Onyibe, Nizar Habash

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	Undefined
Title of host publication	Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Place of Publication	Vancouver, Canada
Publisher	Association for Computational Linguistics (ACL)
Pages	670-674
Number of pages	5
DOIs	https://doi.org/10.18653/v1/S17-2111
State	Published - Aug 1 2017

Access to Document

10.18653/v1/S17-2111

https://www.aclweb.org/anthology/S17-2111

Cite this

OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields. / Onyibe, Chukwuyem; Habash, Nizar.
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017). Vancouver, Canada: Association for Computational Linguistics (ACL), 2017. p. 670-674.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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