JOURNAL ARTICLE
Muslim Women's Religious Leadership in the Digital Age: How Online Platforms Transform Traditional Authority Struc-Tures.
Published In: African Journal of Gender, Society & Development, 2026, v. 15, n. 1. P. 203 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Mudau, Ndidzulafhi; Mudau, Thizwilondi Josephine 3 of 3
Abstract
The article examines how digital technologies are transforming Muslim women's access to religious leadership by enabling them to circumvent traditional institutional and theological barriers rooted in patriarchal interpretations of Islam. Utilizing a systematic review of 178 scholarly sources, the study highlights that Muslim women employ online platforms—such as blogs, social media, and virtual study groups—to assert interpretive authority through ijtihad, build transnational feminist networks, and create alternative religious spaces beyond male-dominated institutions. Framed within liberal feminist philosophy, the research underscores the negotiation between maintaining Islamic authenticity and promoting gender justice, while also addressing challenges like digital divides, online harassment, and institutional resistance. The findings suggest that digital empowerment fosters hybrid models of religious authority based on lived experience and community recognition rather than formal credentials, offering practical implications for Islamic communities to integrate women's digital leadership within traditional frameworks.
Additional Information
- Source:African Journal of Gender, Society & Development. 2026/03, Vol. 15, Issue 1, p203
- Document Type:Article
- Subject Area:Law
- Publication Date:2026
- ISSN:2634-3614
- DOI:10.31920/2634-3622/2026/v15n1a9
- Accession Number:192859170
- Copyright Statement:Copyright of African Journal of Gender, Society & Development is the property of Adonis & Abbey Publishers Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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