ArMeme: Propagandistic Content in Arabic Memes
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909336796659712 |
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| author | Alam, Firoj Hasnat, Abul Ahmed, Fatema Hasan, Md Arid Hasanain, Maram |
| author_facet | Alam, Firoj Hasnat, Abul Ahmed, Fatema Hasan, Md Arid Hasanain, Maram |
| contents | With the rise of digital communication, memes have become a significant medium for cultural and political expression that is often used to mislead audiences. Identification of such misleading and persuasive multimodal content has become more important among various stakeholders, including social media platforms, policymakers, and the broader society as they often cause harm to individuals, organizations, and/or society. While there has been effort to develop AI-based automatic systems for resource-rich languages (e.g., English), it is relatively little to none for medium to low resource languages. In this study, we focused on developing an Arabic memes dataset with manual annotations of propagandistic content. We annotated ~6K Arabic memes collected from various social media platforms, which is a first resource for Arabic multimodal research. We provide a comprehensive analysis aiming to develop computational tools for their detection. We will make them publicly available for the community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_03916 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ArMeme: Propagandistic Content in Arabic Memes Alam, Firoj Hasnat, Abul Ahmed, Fatema Hasan, Md Arid Hasanain, Maram Computation and Language Artificial Intelligence Computer Vision and Pattern Recognition 68T50 I.2.7 With the rise of digital communication, memes have become a significant medium for cultural and political expression that is often used to mislead audiences. Identification of such misleading and persuasive multimodal content has become more important among various stakeholders, including social media platforms, policymakers, and the broader society as they often cause harm to individuals, organizations, and/or society. While there has been effort to develop AI-based automatic systems for resource-rich languages (e.g., English), it is relatively little to none for medium to low resource languages. In this study, we focused on developing an Arabic memes dataset with manual annotations of propagandistic content. We annotated ~6K Arabic memes collected from various social media platforms, which is a first resource for Arabic multimodal research. We provide a comprehensive analysis aiming to develop computational tools for their detection. We will make them publicly available for the community. |
| title | ArMeme: Propagandistic Content in Arabic Memes |
| topic | Computation and Language Artificial Intelligence Computer Vision and Pattern Recognition 68T50 I.2.7 |
| url | https://arxiv.org/abs/2406.03916 |