research-article

A Systematic Review on Hadith Authentication and Classification Methods

Authors:

Farid Binbeshr,

Amirrudin Kamsin,

Manal MohammedAuthors Info & Claims

Transactions on Asian and Low-Resource Language Information Processing, Volume 20, Issue 2

Article No.: 34, Pages 1 - 17

https://doi.org/10.1145/3434236

Published: 23 April 2021 Publication History

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Abstract

Background: A hadith refers to sayings, actions, and characteristics of the Prophet Muhammad peace be upon him. The authenticity of hadiths is crucial, because they constitute the source of legislation for Muslims with the Holy Quran. Classifying hadiths into groups is a matter of importance as well, to make them easy to search and recognize.

Objective: To report the results of a systematic review concerning hadith authentication and classification methods.

Data sources: Original articles found in ACM, IEEE Xplore, ScienceDirect, Scopus, Web of Science, Springer Link, and Wiley Online Library.

Study selection criteria: Only original articles written in English and dealing with hadith authentication and classification. Reviews, editorial, letters, grey literature, and restricted or incomplete articles are excluded.

Data extraction: Two authors were assigned to extract data using a predefined data extraction form to answer research questions and assess studies quality.

Results: A total of 27 studies were included in this review. There are 14 studies in authentication and 13 studies in classification. Most of the selected studies (17 of 27) were published in conferences, while the others (10 of 27) were published in scientific journals. Research in the area of hadith authentication and classification has received more attention in recent years (2016–2019).

Conclusions: Hadith authentication methods are classified into machine learning, rule-based, and a hybrid of rule-based and machine learning and rule-based and statistical methods. Hadith classification methods are classified into machine learning and rule-based. All classification studies used Matn, while the majority of authentication studies used isnad. As a dataset source, Sahih Al-Bukhari was used by most studies. None of the used datasets is publicly available as a benchmark dataset, either in hadith authentication or classification. Recall and Precision are the most frequent evaluation metrics used by the selected studies.

References

[1]

Hammam M. Abdelaal, Berihan R. Elemary, and Hassan A. Youness. 2019. Classification of hadith according to its content based on supervised learning algorithms. IEEE Access 7 (2019), 152379–152387.

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