YouTube video trends to provide content creators with data-driven strategies for enhanced performance
Akshitha Katyaini Reddy Akkireddy (Northwest Missouri State University), Sai Swetha Bodlapati (Northwest Missouri State University), Isam Alobaidi (Northwest Missouri State University)
This analysis investigates YouTube video trends to provide content creators with data-driven strategies for enhanced performance. By leveraging a dataset of video details and utilizing PySpark for efficient data processing, the study identifies optimal posting times, popular content categories, and the influence of metadata like tags and titles on viewer engagement. Regional performance variations and engagement metrics, such as like-to-view and comment-to-view ratios, are also explored. The resulting insights empower creators to refine their posting schedules and content strategies for increased viewership and interaction. This study facilitates a deeper understanding of audience behavior and content effectiveness, ultimately aiming to bridge the gap between creative content and successful audience engagement on the YouTube platform.