Detecting Misinformation Using Multimodal AI Models on Social Media Platforms

Abstract: Misinformation on social media has become a critical challenge, impacting public opinion, health, and democracy. Traditional text-based methods for misinformation detection often fall short because social media content is increasingly multimodal, containing images, videos, and text. This paper explores the use of multimodal AI models that integrate visual, textual, and contextual features to improve the accuracy of misinformation detection on social media platforms. We present an overview of recent advancements, propose a multimodal framework, and discuss experimental results, challenges, and future research directions.

Multimodal Fusion, Natural Language Processing, Multimodal AI, Social Network Analysis, Deepfake Detection

1. Aronoff, S. (1989). Geographic Information Systems: A Management Perspective. Ottawa: WDL Publications. [Google Scholar] [Crossref]

2. Jin, Z., Cao, J., Guo, H., Zhang, Y., & Luo, J. (2017). Multimodal fusion with recurrent neural networks for rumor detection on microblogs. ACM Multimedia. [Google Scholar] [Crossref]

3. Kiela, D., Bulat, L., & Clark, S. (2019). Learning Multimodal Representations with Sparse Attention. arXiv preprint arXiv:1902.00751. [Google Scholar] [Crossref]

4. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. NAACL. [Google Scholar] [Crossref]

5. Lu, J., Batra, D., Parikh, D., & Lee, S. (2019). VilBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks. NeurIPS. [Google Scholar] [Crossref]

6. Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake News Detection on Social Media: A Data Mining Perspective. ACM SIGKDD Explorations. [Google Scholar] [Crossref]

7. Wang, Y., Ma, F., Jin, Z., Yuan, Y., Xun, G., Jha, K., & Gao, J. (2018). EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection. KDD. [Google Scholar] [Crossref]

• Topology Optimization for Low-Power-Wide-Area Networks (LPWANs) within Internet of Things (IOT)
• Enhanced Face Detection Using Haar Cascade with Histogram Equalization, Sharpening, and Denoising for Real-Time Applications
• The Evolution of Data Analytics and Its Future Implication
• Utilizing AI Approaches for Generating Code Automatically
• Practicing Continuous Integration Continuous Delivery on AWS