Text-Based Causal Inference on Irony and Sarcasm Detection

Çekinel R. F., Karagöz P.

24th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2022, Vienna, Avusturya, 22 - 24 Ağustos 2022, cilt.13428 LNCS, ss.31-45 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 13428 LNCS
  • Doi Numarası: 10.1007/978-3-031-12670-3_3
  • Basıldığı Şehir: Vienna
  • Basıldığı Ülke: Avusturya
  • Sayfa Sayıları: ss.31-45
  • Anahtar Kelimeler: Irony detection, Causal inference, Clustering, Topic modeling, LANGUAGE
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The state-of-the-art NLP models’ success advanced significantly as their complexity increased in recent years. However, these models tend to consider the statistical correlation between features which may lead to bias. Therefore, to build robust systems, causality should be considered while estimating the given task’s data generating process. In this study, we explore text-based causal inference on the irony and sarcasm detection problem. Additionally, we model the latent confounders by performing unsupervised data analysis, particularly clustering and topic modeling. The obtained results also provide insight for the causal explainability in irony detection.