Analyzing Educational Content on YouTube: Trends, User Behavior, and Recommendation Strategies
Jayavardhini P1, Mahalakame RM2, Srinivetha P3, Eugene Berna I4
1 UG Scholar, Information Science and Engineering & Bannari Amman Institute of Technology
2 UG Scholar, Information Science and Engineering & Bannari Amman Institute of Technology
3 UG Scholar, Information Science and Engineering & Bannari Amman Institute of Technology
4 Assistant Professor, Artificial Intelligence and Machine Learning & Bannari Amman Institute of Technology
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Abstract - Our research journey took us deep into the realm of educational content on YouTube, a platform known for learning and exploration. We aimed to uncover patterns and trends in educational videos and use this knowledge to enhance the user experience through content recommendations. Using specialized tools, we analyzed data collected directly from YouTube. One intriguing finding was the varying lifespans of trending videos in different countries. Some videos enjoyed extended fame, while others had a shorter time in the spotlight. This cultural diversity in video lifecycles fascinated us. We also discovered rich user engagement across the globe by examining likes, dislikes, views, and comments. Different countries showed preferences in expressing themselves through engagement metrics. Science, technology, and practical tutorials consistently ranked highly in educational categories. We also found that the timing of content publication played a crucial role in a video's success. Understanding this correlation can guide content creators in maintaining relevance. Additionally, sentiment analysis revealed emotional tones associated with video tags, providing insights into what resonates with viewers. We also determined the best time for educational video consumption, based on user behavior and engagement. Finally, we implemented recommendation algorithms, combining collaborative and content-based filtering, to personalize the learning experience on YouTube. Overall, our research sheds light on the multifaceted world of educational content and provides guidance for creators and learners on this dynamic platform. As YouTube evolves, our findings will continue to shape the path towards a more engaging educational future.
Key Words: YouTube, Educational Content, Trend Analysis, User Behavior, Recommendation Algorithms, Data Analysis, Video Trends, User Engagement.
