Proposal of a Data Augmentation Method Using ChatGPT for Japanese Imbalanced Data2024 · As the exploitation of large-scale data advances, numerous classification issues are being effectively addressed. However, significant challenges persist when dealing with imbalanced data. In cases of data imbalance, ideally, new data would be annotated for the underrepresented categories. Nonetheless, in practical terms, data augmentation strategies are often employed to generate analogous data for these minor categories. While there are numerous issues associated with data augmentation techniques within the realm of natural language processing, no definitive methods have been established until the efficacy of ChatGPT for English data augmentation was demonstrated. However, it is known that its performance decreases for languages other than English, and there has been limited validation in Japanese. Consequently, in this research, we sought to annotate and augment the Livedoor News Corpus using ChatGPT, and through a comparative analysis of accuracy changes, we validated the effectiveness of ChatGPT for Japanese imbalanced data.
