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.
Cite
CITATION STYLE
Dovdon, E., & Saias, J. (2017). ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 644–647). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s17-2106
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