International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Multi-Modal AI Frameworks: The Next Frontier in Combating Social Media Misinformation |
|---|---|
| ABSTRACT | The rapid growth of social media has transformed how information is created and consumed, but it has also enabled the widespread dissemination of fake news. This misinformation poses a significant threat to democratic systems, public safety, and societal trust. Traditional fake news detection systems rely primarily on textual analysis using Natural Language Processing (NLP), which is no longer sufficient in the era of multi-modal misinformation involving images, videos, and contextual manipulation. This research proposes a multi-modal AI framework that integrates textual, visual, and social context analysis. The model combines RoBERTa embeddings for text understanding, CLIP-based visual analysis for image-text alignment, and Graph Neural Networks (GNNs) for analyzing information propagation. Experimental results demonstrate that multi-modal fusion significantly outperforms unimodal approaches, achieving accuracy levels up to 95–99%. |
| AUTHOR | NAYAN VIJAY PATIL Dr. D.Y. Patil Arts, Commerce and Science College, Akurdi, Pune, Maharashtra, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404071 |
| pdf/71_Multi-Modal AI Frameworks The Next Frontier in Combating Social Media Misinformation.pdf | |
| KEYWORDS | |
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