Deradicalizing YouTube: Characterization, Detection, and Personalization of Religiously Intolerant Arabic Videos Conference Proceeding uri icon



  • Growing evidence suggests that YouTube's recommendation algorithm plays a role in online radicalization via surfacing extreme content. Radical Islamist groups, in particular, have been profiting from the global appeal of YouTube to disseminate hate and jihadist propaganda. In this quantitative, data-driven study, we investigate the prevalence of religiously intolerant Arabic YouTube videos, the tendency of the platform to recommend such videos, and how these recommendations are affected by demographics and watch history. Based on our deep learning classifier developed to detect hateful videos and a large-scale dataset of over 350K videos, we find that Arabic videos targeting religious minorities are particularly prevalent in search results (30%) and first-level recommendations (21%), and that 15% of overall captured recommendations point to hateful videos. Our personalized audit experiments suggest that gender and religious identity can substantially affect the extent of exposure to hateful content. Our results contribute vital insights into the phenomenon of online radicalization and facilitate curbing online harmful content.

publication date

  • November 7, 2022

has restriction

  • bronze

Date in CU Experts

  • February 3, 2023 12:22 PM

Full Author List

  • Albadi N; Kurdi M; Mishra S

author count

  • 3

Other Profiles

Electronic International Standard Serial Number (EISSN)

  • 2573-0142

Additional Document Info

start page

  • 1

end page

  • 25


  • 6


  • CSCW2