ECNU at SemEval-2018 Task 2: Leverage Traditional NLP Features and Neural Networks Methods to Address Twitter Emoji Prediction Task

Xingwu Lu, Xin Mao, Man Lan, Yuanbin Wu


Abstract
This paper describes our submissions to Task 2 in SemEval 2018, i.e., Multilingual Emoji Prediction. We first investigate several traditional Natural Language Processing (NLP) features, and then design several deep learning models. For subtask 1: Emoji Prediction in English, we combine two different methods to represent tweet, i.e., supervised model using traditional features and deep learning model. For subtask 2: Emoji Prediction in Spanish, we only use deep learning model.
Anthology ID:
S18-1068
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
433–437
Language:
URL:
https://aclanthology.org/S18-1068
DOI:
10.18653/v1/S18-1068
Bibkey:
Cite (ACL):
Xingwu Lu, Xin Mao, Man Lan, and Yuanbin Wu. 2018. ECNU at SemEval-2018 Task 2: Leverage Traditional NLP Features and Neural Networks Methods to Address Twitter Emoji Prediction Task. In Proceedings of The 12th International Workshop on Semantic Evaluation, pages 433–437, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
ECNU at SemEval-2018 Task 2: Leverage Traditional NLP Features and Neural Networks Methods to Address Twitter Emoji Prediction Task (Lu et al., SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1068.pdf