UBC-NLP at SemEval-2019 Task 6:Ensemble Learning of Offensive Content With Enhanced Training Data

Arun Rajendran, Chiyu Zhang, Muhammad Abdul-Mageed

We examine learning offensive content on Twitter with limited, imbalanced data. For the purpose, we investigate the utility of using various data enhancement methods with a host of classical ensemble classifiers. Among the 75 participating teams in SemEval-2019 sub-task B, our system ranks 6th (with 0.706 macro F1-score). For sub-task C, among the 65 participating teams, our system ranks 9th (with 0.587 macro F1-score).

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