Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866929630478336000 |
|---|---|
| author | Ahmed, Ahmed Haj Yew, Rui-Jie Minocher, Xerxes Venkatasubramanian, Suresh |
| author_facet | Ahmed, Ahmed Haj Yew, Rui-Jie Minocher, Xerxes Venkatasubramanian, Suresh |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_10991 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection Ahmed, Ahmed Haj Yew, Rui-Jie Minocher, Xerxes Venkatasubramanian, Suresh Computation and Language Artificial Intelligence Computers and Society 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. |
| title | Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection |
| topic | Computation and Language Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2412.10991 |