Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification

Juan Manuel Pérez, Franco M. Luque


Abstract
In this article, we describe our participation in HatEval, a shared task aimed at the detection of hate speech against immigrants and women. We focused on Spanish subtasks, building from our previous experiences on sentiment analysis in this language. We trained linear classifiers and Recurrent Neural Networks, using classic features, such as bag-of-words, bag-of-characters, and word embeddings, and also with recent techniques such as contextualized word representations. In particular, we trained robust task-oriented subword-aware embeddings and computed tweet representations using a weighted-averaging strategy. In the final evaluation, our systems showed competitive results for both Spanish subtasks ES-A and ES-B, achieving the first and fourth places respectively.
Anthology ID:
S19-2008
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
64–69
Language:
URL:
https://aclanthology.org/S19-2008
DOI:
10.18653/v1/S19-2008
Bibkey:
Cite (ACL):
Juan Manuel Pérez and Franco M. Luque. 2019. Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 64–69, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
Atalaya at SemEval 2019 Task 5: Robust Embeddings for Tweet Classification (Pérez & Luque, SemEval 2019)
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PDF:
https://aclanthology.org/S19-2008.pdf