Fabricated Hadith Detection: A Novel Matn-Based Approach With Transformer Language Models

Muslims rely primarily on the Quran and the Hadiths in all their spiritual life and consider them as sacred sources. If the Quran is God's word, then the Hadiths are God's instructions in the words of the Prophet Muhammad. Since Hadiths are transmitted through multiple narrators, they have...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2022, Vol.10, p.113330-113342
Main Authors: Gaanoun, Kamel, Alsuhaibani, Mohammed
Format: Article
Language:English
Subjects:
Arabic NLP
Authentication
BERT
Bit error rate
Classification algorithms
fabricated Hadiths
Fabrication
Hadtih authentication
Mawdu
Text categorization
Time-domain analysis
Time-varying systems
Transformers
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Muslims rely primarily on the Quran and the Hadiths in all their spiritual life and consider them as sacred sources. If the Quran is God's word, then the Hadiths are God's instructions in the words of the Prophet Muhammad. Since Hadiths are transmitted through multiple narrators, they have been extensively studied to ensure their authenticity. The purpose of this study is to detect fabricated Hadiths, or Mawdu, which is the type of Hadith most rejected by Muslim scholars. The study utilises the central text and content of Hadith, Matn, rather than solely focusing on Hadith chain of narrators, Sanad. In order to accomplish this, we create and release the first dataset dedicated to Mawdu Hadiths, called MAHADDAT. Furthermore, we set up a Mawdu Hadith (MH) detection system based on a transformer language model, BERT, achieving a 92.47% \text{F}1_{MH} score.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2022.3217457