DWReCO at CheckThat! 2023: Enhancing Subjectivity Detection through
  Style-based Data Sampling
Ipek Baris Schlicht Lynn Khellaf Defne Altiok
This paper describes our submission for the subjectivity detection task at
the CheckThat! Lab. To tackle class imbalances in the task, we have generated
additional training materials with GPT-3 models using prompts of different
styles from a subjectivity checklist based on journalistic perspective. We used
the extended training set to fine-tune language-specific transformer models.
Our experiments in English, German and Turkish demonstrate that different
subjective styles are effective across all languages. In addition, we observe
that the style-based oversampling is better than paraphrasing in Turkish and
English. Lastly, the GPT-3 models sometimes produce lacklustre results when
generating style-based texts in non-English languages.