Insult Detection in the Turkish Language Through Different Machine Learning Algorithms

In this research paper, we propose to use the Turkish Court of Cassation- Yargitay- cases to build a dataset for insult detection tasks and compare machine learning models trained on this dataset. We accumulated studies available in the literature compiling Court of Cassation cases and generated a train and test set for testing machine learning algorithms for insult detection. Although machine learning is not capable of understanding the legal context, cultural background, and the nature of insults or non-insults, it can help identify insults with proper training data created by experts. As far as for the authors knowledge this is the first study to use machine learning for the purpose of automatically distinguishing between insult and non-insult cases within the Turkish justice system. Our research, though its is in its first steps, represents a significant contribution to the field, as it addresses a gap in the existing literature and provides a machine learning approach to improving the efficiency and accuracy of legal decision-making.