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: Contribution to conference › Paper › peer-review

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	English (US)
Number of pages	5
DOIs	https://doi.org/10.18653/v1/s17-2111
State	Published - 2018

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title = "OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields",

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.",

author = "Chukwuyem Onyibe and Nizar Habash",

year = "2018",

doi = "10.18653/v1/s17-2111",

language = "English (US)",

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AU - Onyibe, Chukwuyem

AU - Habash, Nizar

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N2 - 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.

AB - 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.

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DO - 10.18653/v1/s17-2111

M3 - Paper

ER -

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

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