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
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
644–647
Language:
URL:
https://www.aclweb.org/anthology/S17-2106
DOI:
10.18653/v1/S17-2106
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-2106.pdf