Detecting Misinformation Using Multimodal AI Models on Social Media Platforms
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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.
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