eISSN 2093-744X
pISSN 1598-2645

Table 7

Comparison table of similar work

Authors	Techniques used	Discussions
Xu Guo et al. [4]	Model: BERT with Latent-Optimization MethodDataset: iSarcasm, Ptacek	F1 Score:iSarcasm: 34.92%SemEval-18: 66.26%Limitation: no data augmentation was performed to balance the iSarcasm dataset.
Amirhossein et al. [16]	Model: BERT-based DataAugmentation: word removalDataset: iSarcasm	F1 Score:iSarcasm: 41.4%Limitation: data augmentation only use word removal, thus reducing sentence quality and potentially remove sarcastic nature of sentence
Our proposed method	Model: BERT, RoBERTa, DistilBERT	F1 Score:iSarcasm: 40.44%Ghosh: 81.08%Ptacek: 87.41%SemEval-18: 67.46%Novelty: data augmentation using GloVe word embedding, data duplication technique and deeper analysis of data augmentation results

International Journal of Fuzzy Logic and Intelligent Systems 2022;22:401~413 https://doi.org/10.5391/IJFIS.2022.22.4.401