Embeddia at SemEval-2019 Task 6: Detecting Hate with Neural Network and Transfer Learning Approaches

Andraž Pelicon, Matej Martinc, Petra Kralj Novak


Abstract
SemEval 2019 Task 6 was OffensEval: Identifying and Categorizing Offensive Language in Social Media. The task was further divided into three sub-tasks: offensive language identification, automatic categorization of offense types, and offense target identification. In this paper, we present the approaches used by the Embeddia team, who qualified as fourth, eighteenth and fifth on the tree sub-tasks. A different model was trained for each sub-task. For the first sub-task, we used a BERT model fine-tuned on the OLID dataset, while for the second and third tasks we developed a custom neural network architecture which combines bag-of-words features and automatically generated sequence-based features. Our results show that combining automatically and manually crafted features fed into a neural architecture outperform transfer learning approach on more unbalanced datasets.
Anthology ID:
S19-2108
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
604–610
Language:
URL:
https://aclanthology.org/S19-2108
DOI:
10.18653/v1/S19-2108
Bibkey:
Cite (ACL):
Andraž Pelicon, Matej Martinc, and Petra Kralj Novak. 2019. Embeddia at SemEval-2019 Task 6: Detecting Hate with Neural Network and Transfer Learning Approaches. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 604–610, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
Embeddia at SemEval-2019 Task 6: Detecting Hate with Neural Network and Transfer Learning Approaches (Pelicon et al., SemEval 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/S19-2108.pdf
Code
 Andrazp/embeddia-semeval2019
Data
OLID