Authenticity detection as a binary text categorization problem: Application to Hadith authentication

Authentication of Hadiths (sayings of Prophet Muhammad) is very important field for religious scholars as well as historians. Authenticity verification is traditionally conducted by studying how trustworthy is each person in the narration chain. In this study, we propose a novel approach completely based on the content of each Hadith. For each category of hadiths (authentic and non-authentic), we create a binary relation in which the hadiths correspond to the objects of the relation and the words correspond to its attributes. Keywords for each category are then obtained in a hierarchical ordering of importance using the hyper rectangular decomposition. Classification is done by feeding the extracted keywords to a logistic regression classifier. The method has been validated on a database of about 1600 hadiths. Results show that classification accuracy increases with the number of annotators who agreed on the authenticity of each hadith. These findings suggest that our method successfully extracts relevant keywords and can be combined with other traditional methods.