Social Medium Video Post

Social media video posts are a rich source of multimodal data, presenting a significant challenge and opportunity for researchers. Current research focuses on developing advanced machine learning models, including large multimodal models (LMMs) and techniques like contrastive learning and masked language modeling, to analyze this data for tasks such as sentiment analysis, misinformation detection, and demographic inference. These efforts are driven by the need to understand the complex interplay of text, images, and video within these posts, with applications ranging from targeted advertising to public health monitoring. The development of large, multilingual, and multi-aspect datasets is crucial for training and evaluating these models, enabling more robust and accurate analysis of social media video content.