Are Foundation Models the Next-Generation Social Media Content Moderators?

Nadeem, Mohammad; Javed, Laeeba; Sohail, Shahab Saquib; Cambria, Erik; Hussain, Amir

Abstract

Recent progress in artificial intelligence (AI) tools and systems has been significant, especially in their reasoning and efficiency. Notable examples include generative AI-based large language models (LLMs) like Generative Pre-trained Transformer 3.5 (GPT-3.5), GPT-4, and Gemini, among others. In our work, we evaluated the effectiveness of fine-tuned deep learning models compared to general-purpose LLMs in moderating image-based content. We used deep learning models such as convolutional neural networks, ResNet50, and VGG-16, trained them for violence detection on an image dataset, and tested them on a separate dataset. The same test dataset was also evaluated using Large Language and Vision Assistant (LLaVa) and GPT-4, two LLMs that can process images. The results demonstrate that VGG-16 model had the highest accuracy at 0.94, while LLaVa had the lowest at 0.66. GPT-4 showed superiority over LLaVa with an accuracy value of 0.9242. LLaVa recorded the highest precision of all models.

Citation

Nadeem, M., Javed, L., Sohail, S. S., Cambria, E., & Hussain, A. (2024). Are Foundation Models the Next-Generation Social Media Content Moderators?. IEEE Intelligent Systems, 39(6), 70-80. https://doi.org/10.1109/mis.2024.3477109

• Journal Article Type: Article
• Online Publication Date: Dec 5, 2024
• Publication Date: 2024-11
• Deposit Date: Dec 17, 2024
• Publicly Available Date: Dec 17, 2024
• Journal: IEEE Intelligent Systems
• Print ISSN: 1541-1672
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 6
• Pages: 70-80
• DOI: https://doi.org/10.1109/mis.2024.3477109