Detecting Hate and Inflammatory Content in Bengali Memes: A New Multimodal Dataset and Co-Attention Framework 文章
详细信息
- 来源站点
- ArXiv CS.CL
- 作者
- Rakib Ullah (Sylhet Engineering College), Mominul islam (Daffodil International University), Md Sanjid Hossain (Daffodil International University), Md Ismail Hossain (Daffodil International University)
- 文章类型
- NEWS
- 语言
- en
- 发布日期
- 2026-06-16
摘要
arXiv:2602.22391v2 Announce Type: replace Abstract: Internet memes have become a dominant form of expression on social media, including within the Bengali speaking community. While often humorous, memes can also be exploited to spread offensive, harmful, and inflammatory content targeting individuals and groups. Detecting this type of content is exceptionally challenging due to its satirical, subtle, and culturally specific nature. This problem is magnified for low-resource languages like Bengali, as existing research predominantly focuses on high-resource languages. To address this critical research gap, we introduce Bn-HIB (Bangla Hate Inflammatory Benign), a novel dataset containing 3,247 manually annotated Bengali memes categorized as Benign, Hate, or Inflammatory. Significantly, Bn- HIB is the first dataset to distinguish inflammatory content from direct hate speech in Bengali memes.