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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM25598

Analyzing Educational Content on YouTube: Trends, User Behavior, and Recommendation Strategies

Stream/Area:

-

Subject:

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Paper ID:

10.55041/IJSREM25598

Volume:

7 |

9 |

Sep 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

JP

Jayavardhini P

MR

Mahalakame RM

SP

Srinivetha P

EBI

Eugene Berna I

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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.

KEYWORDS

YouTube Educational Content Trend Analysis User Behavior Recommendation Algorithms Data Analysis Video Trends User Engagement.

Cite This Article

Jayavardhini P, Mahalakame RM, Srinivetha P, Eugene Berna I, "Analyzing Educational Content on YouTube: Trends, User Behavior, and Recommendation Strategies," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 9, Sep 2023. https://doi.org/10.55041/IJSREM25598

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Publication Date

8/8/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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