Abstract
This paper describes the participation of ELiRF-UPV team at task 4 of SemEval2017. Our approach is based on the use of convolutional and recurrent neural networks and the combination of general and specific word embeddings with polarity lexicons. We participated in all of the proposed subtasks both for English and Arabic languages using the same system with small variations.- Anthology ID:
- S17-2121
- 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:
- 723–727
- Language:
- URL:
- https://aclanthology.org/S17-2121
- DOI:
- 10.18653/v1/S17-2121
- Cite (ACL):
- José-Ángel González, Ferran Pla, and Lluís-F. Hurtado. 2017. ELiRF-UPV at SemEval-2017 Task 4: Sentiment Analysis using Deep Learning. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 723–727, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- ELiRF-UPV at SemEval-2017 Task 4: Sentiment Analysis using Deep Learning (González et al., SemEval 2017)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/S17-2121.pdf