TOPIC MODELING IN THE HOLY QURAN USING BERTopic
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Date
2025-06-15
Journal Title
Journal ISSN
Volume Title
Publisher
Mohamed Boudiaf University of M'sila
Abstract
This research applies topic modeling to the Holy Quran using BERTopic and LaBSE
embeddings to automatically extract and classify its main themes. The Qurans thematic
complexity requires advanced NLP techniques. The study organizes verses into three
categories: Monotheism, Legal Rulings, and Stories. Results show that this AI-based
approach supports deeper understanding and thematic analysis of Quranic content.
Description
Keywords
topic modeling, Holy Quran, Arabic NLP, BERTopic, LaBSE