Youtube Trending Video Metadata Analysis Using Machine Learning - S. Amudha 1, V R. Niveditha, Dr. P.S. Raja Kumar , M.Revathi , Dr.S.Radha Rammohan (International Journal of Advanced Science and Technology, 2020)
Data Analysis and Mining are becoming indispensable part of every major organization tofind recent trends and statistics and formulate business strategies, planning and marketing.However, most of the Data generated is generally in Huge Size and comes in unstructuredformat. Big Data cannot be analyzed by traditional database systems and processes. To resolvethis issue, many new tools that implement Parallel Processing are being deployed in theseorganizations. As part of the Advanced Databases Project, we propose to perform Data Analysisof YouTube data. We extracted data of 5 Million Video records from YouTube API andperformed Data Analysis on the data to insight into latest trends and user engagement inYouTube with respect to Categories and Year. Data Analysis and Visualization was done usingAnaconda jupyter Notebook. Analysis of structured data has seen tremendous success in the past.However, analysis of large scale unstructured data in the form of video format remains achallenging area. YouTube, a Google company, has over a billion users and generates billions ofviews. Since YouTube data is getting created in a very huge amount and with an equally greatspeed, there is a huge demand to store, process and carefully study this large amount of data tomake it usable.