International Journal of Innovative Research in                 Electrical, Electronics, Instrumentation and Control Engineering

A monthly peer-reviewed journal

ISSN Online 2321-2004
ISSN Print 2321-5526

Since  2013

Abstract: Online video streaming platforms are heavily used nowadays. Websites such as YouTube offers content creators a great platform to share their knowledge, ideas and interesting information to their viewers. For a video to reach to maximum people, YouTube offers a trending page on website that shows videos which are trending at that particular time. Other than few viral videos that achieve high view count which are predictable to end up in trending section, rest of the videos cannot be predicted. Corporate companies are using social media for improving their businesses, the data mining and analysis are very important in these days. This paper deals with analysis of YouTube Data on Trending Videos. The analysis is done using user features such as Views, Comments, Likes, and Dislikes. Analysis can be performed using algorithms like Linear Regression, classification and navi bayes algorithm and python libraries like pandas, matplot library to classify the YouTube Data and obtain useful information.

Keywords: YouTube trending, Trending videos, likes.

PDF | DOI: 10.17148/IJIREEICE.2022.10740

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