Stylometric model for detecting oath expressions: A case study for Quranic texts
Ahmad Alqurneh, Aida Mustapha, Masrah Azrifah Azmi Murad, Nurfadhlina Mohd Sharef · Digital Scholarship in the Humanities · 2014
The Quranic oath is God’s emphasizing the importance or truthfulness of a concept. Oaths are multifaceted, rich expressions, in which a single oath contains a line of meaning and a variety of aspects. This study proposes a new stylometric model for detecting apparent and narrative oaths. Toward this end, two types of application-specific features from a stylometric perspective—structural and content-specific features—were examined. The stylometric features were extracted, and a Bayesian network was constructed to model such features. The stylometric model of oaths was then evaluated through a series of machine-learning experiments using various classifiers: the Bayesian network, a decision tree, instance-based learning, and a neural network. These classification experiments focused on applying stylometric features in apparent and narrative oaths. The experiments covered two datasets: the entire Quran and the smaller dataset of Juz ’ ‘ Amma . The results led to two main conclusions. First, stylometric application-specific features are best used in their entirety—both structural-based and content-specific—rather than as two separate entities. Second, applying stylometric features was more significant in Juz ’ ‘ Amma , in which 40% of its surahs (chapters) contain oath statements. Finally, the stylometric model was extended for oath styles detection using three additional stylometric features—syntactic, character, and lexical, and it was analyzed using statistical approach.