nlpUP at SemEval-2019 Task 6: A Deep Neural Language Model for Offensive Language Detection

Jelena Mitrović, Bastian Birkeneder, Michael Granitzer


Abstract
This paper presents our submission for the SemEval shared task 6, sub-task A on the identification of offensive language. Our proposed model, C-BiGRU, combines a Convolutional Neural Network (CNN) with a bidirectional Recurrent Neural Network (RNN). We utilize word2vec to capture the semantic similarities between words. This composition allows us to extract long term dependencies in tweets and distinguish between offensive and non-offensive tweets. In addition, we evaluate our approach on a different dataset and show that our model is capable of detecting online aggressiveness in both English and German tweets. Our model achieved a macro F1-score of 79.40% on the SemEval dataset.
Anthology ID:
S19-2127
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:
722–726
Language:
URL:
https://www.aclweb.org/anthology/S19-2127
DOI:
10.18653/v1/S19-2127
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PDF:
http://aclanthology.lst.uni-saarland.de/S19-2127.pdf