Abstract
The advent of social media has brought along a novel way of communication where meaning is composed by combining short text messages and visual enhancements, the so-called emojis. We describe our system for participating in SemEval-2018 Task 2 on Multilingual Emoji Prediction. Our approach relies on combining a rich set of various types of features: semantic and metadata. The most important types turned out to be the metadata feature. In subtask 1: Emoji Prediction in English, our primary submission obtain a MAP of 16.45, Precision of 31.557, Recall of 16.771 and Accuracy of 30.992.- Anthology ID:
- S18-1065
- 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:
- 419–422
- Language:
- URL:
- https://aclanthology.org/S18-1065
- DOI:
- 10.18653/v1/S18-1065
- Cite (ACL):
- Yufei Xie and Qingqing Song. 2018. EICA Team at SemEval-2018 Task 2: Semantic and Metadata-based Features for Multilingual Emoji Prediction. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 419–422, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- EICA Team at SemEval-2018 Task 2: Semantic and Metadata-based Features for Multilingual Emoji Prediction (Xie & Song, SemEval 2018)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/S18-1065.pdf