This paper describes our system designed for SemEval 2019 Task 5 “Shared Task on Multilingual Detection of Hate”. We only participate in subtask-A in English. To address this task, we present a stacked BiGRU model based on a capsule network system. In order to convert the tweets into corresponding vector representations and input them into the neural network, we use the fastText tools to get word representations. Then, the sentence representation is enriched by stacked Bidirectional Gated Recurrent Units (BiGRUs) and used as the input of capsule network. Our system achieves an average F1-score of 0.546 and ranks 3rd in the subtask-A in English.
CITATION STYLE
Ding, Y., Zhou, X., & Zhang, X. (2019). YNU DYX at SemEval-2019 task 5: A stacked BiGRU model based on capsule network in detection of hate. In NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop (pp. 535–539). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s19-2096
Mendeley helps you to discover research relevant for your work.