Abstract
This paper presents a system developed during our participation (team name: scmhl5) in the TRAC-2 Shared Task on aggression identification. In particular, we participated in English Sub-task A on three-class classification (‘Overtly Aggressive’, ‘Covertly Aggressive’ and ‘Non-aggressive’) and English Sub-task B on binary classification for Misogynistic Aggression (‘gendered’ or ‘non-gendered’). For both sub-tasks, our method involves using the pre-trained Bert model for extracting the text of each instance into a 768-dimensional vector of embeddings, and then training an ensemble of classifiers on the embedding features. Our method obtained accuracy of 0.703 and weighted F-measure of 0.664 for Sub-task A, whereas for Sub-task B the accuracy was 0.869 and weighted F-measure was 0.851. In terms of the rankings, the weighted F-measure obtained using our method for Sub-task A is ranked in the 10th out of 16 teams, whereas for Sub-task B the weighted F-measure is ranked in the 8th out of 15 teams.- Anthology ID:
- 2020.trac-1.10
- Volume:
- Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Ritesh Kumar, Atul Kr. Ojha, Bornini Lahiri, Marcos Zampieri, Shervin Malmasi, Vanessa Murdock, Daniel Kadar
- Venue:
- TRAC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 62–68
- Language:
- English
- URL:
- https://aclanthology.org/2020.trac-1.10
- DOI:
- Cite (ACL):
- Han Liu, Pete Burnap, Wafa Alorainy, and Matthew Williams. 2020. Scmhl5 at TRAC-2 Shared Task on Aggression Identification: Bert Based Ensemble Learning Approach. In Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying, pages 62–68, Marseille, France. European Language Resources Association (ELRA).
- Cite (Informal):
- Scmhl5 at TRAC-2 Shared Task on Aggression Identification: Bert Based Ensemble Learning Approach (Liu et al., TRAC 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.trac-1.10.pdf