{"title":"YouTube Trend Analysis","authors":"Arushi Pathik, Saumya Patni, Vaibhav Patel, Jash Patel, Artika Singh","doi":"10.1109/PuneCon55413.2022.10014717","DOIUrl":null,"url":null,"abstract":"Nowadays, Online video streaming services are extremely popular. YouTube give facility to their content creators to spread their knowledge, thoughts, and interesting content with users. In YouTube there is a trending section which shows currently most popular videos, ensuring that a video reaches the widest possible audience. Other than those videos rest are unpredictable, with the exception of few viral videos having a large number of views and are guaranteed to be in the trending section. Data analysis and Data mining are critical in today's world, and businesses are improving their operations by using social media. The aim of paper is to investigate YouTube's trending videos data. Users in the app use Views, Comments, Likes, and Dislikes. Classification algorithms like Linear Regression, Decision Tree, many other Machine Learning models can be used by using Python libraries like pandas and matplotlib, to classify and analyze YouTube data, as well as collect useful information.","PeriodicalId":258640,"journal":{"name":"2022 IEEE Pune Section International Conference (PuneCon)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Pune Section International Conference (PuneCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PuneCon55413.2022.10014717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Nowadays, Online video streaming services are extremely popular. YouTube give facility to their content creators to spread their knowledge, thoughts, and interesting content with users. In YouTube there is a trending section which shows currently most popular videos, ensuring that a video reaches the widest possible audience. Other than those videos rest are unpredictable, with the exception of few viral videos having a large number of views and are guaranteed to be in the trending section. Data analysis and Data mining are critical in today's world, and businesses are improving their operations by using social media. The aim of paper is to investigate YouTube's trending videos data. Users in the app use Views, Comments, Likes, and Dislikes. Classification algorithms like Linear Regression, Decision Tree, many other Machine Learning models can be used by using Python libraries like pandas and matplotlib, to classify and analyze YouTube data, as well as collect useful information.
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