Download pdf
The research of the factors that influence the popularity of YouTube videos
- 1 Nexus International School, 387293, Singapore
* Author to whom correspondence should be addressed.
Abstract
A variety of factors contribute to the multifaceted phenomenon of YouTube video popularity. An understanding of these factors is essential for content providers, marketers, and platform designers to enhance audience engagement and enjoyment. The objective of this study is to examine the critical factors that influence the popularity of YouTube videos, including thumbnail design, video content, title and description optimization, audience participation, and social media marketing. This study aims to analyze the main determinants of YouTube video popularity and offer practical recommendations for enhancing video performance. This paper uses correlation analysis and multiple linear regression on this problem. This will be achieved via an extensive assessment of relevant literature and the use of statistical analysis. The results shows that there are several significant variables that influence the popularity of YouTube videos. The results will facilitate a deeper understanding of the patterns in which digital material is consumed and provide practical suggestions for improving the exposure of films and retaining audience attention on YouTube.
Keywords
YouTube, video popularity, content analysis, viewer engagement, social media promotion.
[1]. Kousha K, Thelwall M and Abdoli M 2012 The Role of Online Videos in Research Communication: A Content Analysis of YouTube Videos Cited in Academic Publications. Journal of the American Society for Information Science and Technology, 63(9), 1710-1727.
[2]. Jang H and Song Y 2017 Clicking Patterns of Thumbnails: Effects of Face Images and Colors on Click-Through Rate. Journal of Visual Communication and Image Representation, 48, 167-176.
[3]. Cunningham S and Craig D 2017 Being ‘Really Real’ on YouTube: Authenticity, Community, and Brand Culture in Social Media Entertainment. Media International Australia, 164(1), 71-81.
[4]. Cha M, Kwak H and Rodriguez P 2007 I Tube, You Tube, Everybody Tubes: Analyzing the World’s Largest User Generated Content Video System. Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, 1-14.
[5]. Zhou R, Khemmarat S and Gao L 2010 The Impact of YouTube Recommendation System on Video Views. Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement, 404-410.
[6]. Pires K and Simon G 2015 YouTube Live and Twitch: A Tour of User-Generated Live Streaming Systems. Proceedings of the 6th ACM Multimedia Systems Conference, 225-230.
[7]. Marchand A, Hennig-Thurau T and Wiertz C 2017 Not All Digital Words of Mouth are Created Equal: Understanding the Respective Impact of Consumer Reviews and Influencer Endorsements. Journal of Marketing Research, 54(4), 601-618.
[8]. Tudor D and Muntean C 2019 Enhancing Educational Videos with Interactive Quizzes to Improve Learning Experience. Journal of Educational Technology Systems, 47(4), 460-475.
[9]. Zhang Z and Liu Y 2016 Understanding the Snowball Effect of User Engagement in Online Social Media. Proceedings of the 25th International Conference on World Wide Web, 1705-1714.
[10]. Susarla A, Oh J H and Tan Y 2012 Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube. Information Systems Research, 23(1), 23-41.
Cite this article
Shen,J. (2024). The research of the factors that influence the popularity of YouTube videos. Theoretical and Natural Science,51,187-193.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of CONF-MPCS 2024 Workshop: Quantum Machine Learning: Bridging Quantum Physics and Computational Simulations
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).