Multimodal Deep Regression on TikTok Content Success

Abstract

Content creators grapple with the challenge of predicting if their investments will lead to increased viewership and audience growth on social media platforms. By employing advanced techniques in video encoding and natural language processing, we construct a powerful multimodal ensemble model for accurately predicting video success. Our preliminary results demonstrate the model’s effectiveness in predicting video virality.