With the proliferation of social networking services (SNS), damage caused by sarcastic and abusive comments has been increasing, creating a demand for technologies that can automatically detect such comments. Among these, comments that use indirect expressions, such as sarcasm, without employing direct language are particularly difficult to detect. In this study, we focus on comments containing positive words as a form of indirect expression, and aim to construct a model capable of detecting sarcastic and abusive comments with higher accuracy than existing models by not only fine-tuning an existing BERT model but also incorporating several techniques such as pattern matching. As a result, we were able to surpass the existing model in all four evaluation metrics: Accuracy, Precision, Recall, and F1.
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- Quote paper
- Go Sato (Author), 2026, Detection of Sarcastic and Abusive Comments Containing Positive Words, Munich, GRIN Verlag, https://www.grin.com/document/1696432
