Document Type

Conference Paper

Publication Date

2024

DOI

10.32473/flairs.37.1.135342

Publication Title

The International FLAIRS Conference Proceedings

Volume

37

Issue

1

Pages

5 pp.

Conference Name

37th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2024, 19-21 May 2024, Miramar Beach, Florida

Abstract

In this paper, we implement a comprehensive three-class system to categorize social media discussions about Islam and Muslims, enhancing the typical binary approach. These classes are: I) General Discourse About Islam and Muslims, II) Criticism of Islamic Teachings and Figures, and III) Comments Against Muslims. These categories are designed to balance the nuances of free speech while protecting diverse groups like Muslims, ex-Muslims, LGBTQ+ communities, and atheists. By utilizing machine learning and employing transformer-based models, we analyze the distribution and characteristics of these classes in social media content. Our findings reveal distinct patterns of user engagement with topics related to Islam, providing valuable insights into the complexities of digital discourse. This research contributes to the fields of quantitative social science by offering an improved method for understanding and moderating online discussions on sensitive religious and cultural subjects.

Rights

© 2024 Esraa Aldreabi, Mukul Dev Chhangani, Khawlah M. Harahsheh, Justin M. Lee, Chung-Hao Chen, Jeremy Blackburn.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Original Publication Citation

Aldreabi, E., Chhangani, M. D., Harahsheh, K. M., Lee, J. M., Chen, C.-H., & Blackburn, J. (2024). Toward inclusivity: Rethinking islamophobic content classification in the digital age. The International FLAIRS Conference Proceedings, 37(1). https://doi.org/10.32473/flairs.37.1.135342

ORCID

0009-0007-3728-1634 (Harahsheh)

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