Abstract
This paper describes the UMDSub system that participated in Task 2 of SemEval-2018. We developed a system that predicts an emoji given the raw text in a English tweet. The system is a Multi-channel Convolutional Neural Network based on subword embeddings for the representation of tweets. This model improves on character or word based methods by about 2%. Our system placed 21st of 48 participating systems in the official evaluation.- Anthology ID:
- S18-1060
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 395–399
- Language:
- URL:
- https://aclanthology.org/S18-1060
- DOI:
- 10.18653/v1/S18-1060
- Cite (ACL):
- Zhenduo Wang and Ted Pedersen. 2018. UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 395–399, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding (Wang & Pedersen, SemEval 2018)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/S18-1060.pdf