JOURNAL ARTICLE

Youtube Trending Videos: Boosting Machine Learning Results Using Exploratory Data Analysis.

  • Published In: Computer Journal, 2023, v. 66, n. 1. P. 35 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Khanam, Sana; Tanweer, Safdar; Khalid, Syed Sibtain 3 of 3

Abstract

This article focuses on the exploratory data analysis (EDA) of YouTube trending video data to uncover patterns in viewership, engagement, and video characteristics that influence trending status. Using a dataset of 40,950 videos collected over 205 days, the study applies statistical and graphical EDA techniques via Python and Jupyter notebooks to analyze numerical and categorical attributes such as views, likes, comments, video titles, and categories. Key findings include a strong positive correlation between views and likes, the predominance of the Entertainment category among trending videos, and the identification of common title words, while attributes like title length showed no significant correlation with popularity. The research highlights EDA's role in improving machine learning model accuracy by providing structured, insightful data and discusses challenges related to big data's volume, variety, and dynamic nature.

Additional Information

  • Source:Computer Journal. 2023/01, Vol. 66, Issue 1, p35
  • Document Type:Article
  • Subject Area:Biography
  • Publication Date:2023
  • ISSN:0010-4620
  • DOI:10.1093/comjnl/bxab142
  • Accession Number:161360862
  • Copyright Statement:Copyright of Computer Journal is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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