ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter

Enkhzol Dovdon, José Saias


Abstract
This paper describes the system we have used for participating in Subtasks A (Message Polarity Classification) and B (Topic-Based Message Polarity Classification according to a two-point scale) of SemEval-2017 Task 4 Sentiment Analysis in Twitter. We used several features with a sentiment lexicon and NLP techniques, Maximum Entropy as a classifier for our system.
Anthology ID:
S17-2106
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
644–647
Language:
URL:
https://aclanthology.org/S17-2106
DOI:
10.18653/v1/S17-2106
Bibkey:
Cite (ACL):
Enkhzol Dovdon and José Saias. 2017. ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 644–647, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter (Dovdon & Saias, SemEval 2017)
Copy Citation:
PDF:
https://aclanthology.org/S17-2106.pdf