The Study on Quranic Surahs' Topic Sameness Using NLP Techniques

Study of the structured-ness of Quranic surahs has attracted the attention of some researchers in recent years. One of the theories herein is the theory of Topic Sameness which acknowledges that the inner elements of surahs have tight relationship with each other and that each surah of Quran has formed on a single core topic. In this paper, we intend to study the topic sameness in Quranic surahs using natural language processing methods. In this regard, based on the two methods of word2vec and Roots' accompaniment in Verses, the similarity of Quranic roots is calculated. Then, the amount of similarity between surahs' title and the concepts within the surahs is studied. Afterwards, the amount of similarity of the concepts within chapters to each other is calculated and compared with the random mode. The results show that the choice of the surah's title is based on rational logic, and that could not have been done by the ordinary public of the early Islamic era. In addition, the surahs hold the inner coherence between the concepts so that they have formed on a single topic or a few topics tightly related to each other.