MODOS at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Weighted SAM, CLIP and ArabianGPT

Abdelhamid Haouhat, Hadda Cherroun, Slimane Bellaouar, Attia Nehar


Abstract
Arabic social media platforms are increasingly using propaganda to deceive or influence people. This propaganda is often spread through multimodal content, such as memes. While substantial research has addressed the automatic detection of propaganda in English content, this paper presents the MODOS team’s participation in the Arabic Multimodal Propagandistic Memes Classification shared task. Our system deploys the Segment Anything Model (SAM) and CLIP for image representation and ARABIAN-GPT embeddings for text. Then, we employ LSTM encoders followed by a weighted fusion strategy to perform binary classification. Our system achieved competitive performance in distinguishing between propagandistic and non-propagandistic memes, scored 0.7290 macro F1, and ranked 6th among the participants.
Anthology ID:
2024.arabicnlp-1.48
Volume:
Proceedings of The Second Arabic Natural Language Processing Conference
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
Venues:
ArabicNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
483–488
Language:
URL:
https://aclanthology.org/2024.arabicnlp-1.48
DOI:
10.18653/v1/2024.arabicnlp-1.48
Bibkey:
Cite (ACL):
Abdelhamid Haouhat, Hadda Cherroun, Slimane Bellaouar, and Attia Nehar. 2024. MODOS at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Weighted SAM, CLIP and ArabianGPT. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 483–488, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
MODOS at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Weighted SAM, CLIP and ArabianGPT (Haouhat et al., ArabicNLP-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.arabicnlp-1.48.pdf