EICA Team at SemEval-2018 Task 2: Semantic and Metadata-based Features for Multilingual Emoji Prediction

Yufei Xie, Qingqing Song


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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/S18-1065.pdf