Detecting Ad Hominem Arguments in Turkish Online Texts: A Study Based on Reddit Political Discussions
2025 IEEE International Conference on Big Data-BigData, Macau, Çin, 8 - 11 Aralık 2025, ss.2766-2773, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/bigdata66926.2025.11401454
- Basıldığı Şehir: Macau
- Basıldığı Ülke: Çin
- Sayfa Sayıları: ss.2766-2773
- Gazi Üniversitesi Adresli: Evet
Özet
Ad hominem arguments are logical fallacies based on direct attacks against a person rather than addressing their viewpoint, and they are frequently encountered in online discussions. These expressions, which have become widespread particularly on social media platforms, disrupt the coherence of debates and may lead to public misinformation. This study aims to automatically detect ad hominem arguments in Turkish online discussions and presents a comparative analysis of different natural language processing approaches in this context. The data collected from the Reddit platform were subjected to cleaning, normalization, and annotation processes and were classified as ad hominem or non-ad hominem. On the resulting dataset, classical machine learning methods (Logistic Regression, Linear SVM) and pre-trained transformer-based deep learning models (BERT, ALBERT, ELECTRA, RoBERTa) were evaluated. The models were compared in terms of accuracy, precision, recall, and F1-score, and each approach was observed to have distinct strengths. The study fills a gap in the literature regarding the automatic detection of logical fallacies in the Turkish language and proposes an applicable and reproducible method for identifying misleading arguments in online discourse.