Revisiting Religious Sectarianism in Nigeria: Sunni and Shia Muslims' Intra-religious Conflict, Impact, and Implications.

  • Published In: International Journal of Religion & Spirituality in Society, 2025, v. 15, n. 1. P. 75 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Edeh, Emmanuel Chidiebere 3 of 3

Abstract

While inter-religious conflict is not new to Nigeria, sectarian competition and conflict between Sunnis and Shias have infiltrated the country and potentially pose a threat to the country's stability. This article does not seek to provide a solution to Nigeria's sectarian conflict between Sunni Islam and Shia Islam, but rather to highlight the dangers it poses to the country through its impact and implications. Through a futurology design approach, the article provides dynamic snapshots of Sunni--Shia sectarian conflict from three dimensions: identity, alliance, and ideology. The article reveals that both Sunni and Shia Islam in Nigeria share a common ideology of establishing Nigeria as an Islamic state. However, they disagree on whose ideology it shall be founded upon owing to their sectarian affiliation with external actors, notably Saudi Arabia and Iran. The article concludes with prognostic reflections on the future political, religious, and social implications for Nigeria if this conflict remains unresolved. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Religion & Spirituality in Society. 2025/03, Vol. 15, Issue 1, p75
  • Document Type:Article
  • Subject Area:Ethnic and Cultural Studies
  • Publication Date:2025
  • ISSN:2154-8633
  • DOI:10.18848/2154-8633/CGP/v15i01/75-97
  • Accession Number:184409895
  • Copyright Statement:Copyright of International Journal of Religion & Spirituality in Society is the property of Common Ground Research Networks 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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