Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection

Ahmed Haj Ahmed, Rui-Jie Yew, Xerxes Minocher, Suresh Venkatasubramanian
12/14/2024
cs.CLcs.AIcs.CY

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Abstract

Social media platforms have become central to global communication, yet they also facilitate the spread of hate speech. For underrepresented dialects like Levantine Arabic, detecting hate speech presents unique cultural, ethical, and linguistic challenges. This paper explores the complex sociopolitical and linguistic landscape of Levantine Arabic and critically examines the limitations of current datasets used in hate speech detection. We highlight the scarcity of publicly available, diverse datasets and analyze the consequences of dialectal bias within existing resources. By emphasizing the need for culturally and contextually informed natural language processing (NLP) tools, we advocate for a more nuanced and inclusive approach to hate speech detection in the Arab world.

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Cite this paper

@article{ahmed2024navigating,
  title  = {Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection},
  author = {Ahmed Haj Ahmed and Rui-Jie Yew and Xerxes Minocher and Suresh Venkatasubramanian},
  year   = {2024},
  eprint = {2412.10991},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.10991v1}
}

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