Liu, Han ORCID: https://orcid.org/0000-0002-7731-8258, Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X, Alorainy, Wafa and Williams, Matthew ORCID: https://orcid.org/0000-0003-2566-6063
2020.
Scmhl5 at TRAC-2 shared task on aggression identification: bert based ensemble learning approach.
Presented at: Second Workshop on Trolling, Aggression and Cyberbullying,
Marseille, France,
16 May 2020.
Proceedings of the Second Workshop on Trolling, Aggression and Cyberbullying.
European Language Resources Association,
pp. 62-68.
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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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Publisher: | European Language Resources Association |
| Date of First Compliant Deposit: | 17 April 2020 |
| Date of Acceptance: | 11 April 2020 |
| Last Modified: | 13 Nov 2025 14:02 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/131040 |
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