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Factors Influencing the Popularity of Youtube Videos and Users’ Decisions to Watch Them

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Factors Influencing the Popularity of Youtube Videos and Users’ Decisions to Watch Them UNIVERSITY OF WOLVERHAMPTON School of Mathematics and Computing Factors influencing the popularity of YouTube videos and users’ decisions to watch them David Foster MSc, MEd A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy School of Mathematics and Computing University of Wolverhampton 2020 This work or any part has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgements, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of David Foster to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature: Date: 7/8/20 1 | P a g e 2 | P a g e Abstract YouTube has substantial impact on modern society as the second most popular website in the world. Despite its sustained popularity, little is known about which types of video are most viewed and the reasons why people choose to watch them. This research critically analyses the sample of videos provided by the YouTube API, then uses the metrics associated with these videos to help assess which types of YouTube video are popular. It also harnesses a questionnaire of mainly UK teacher education graduate YouTube users to investigate which factors influence decisions to watch YouTube videos. This was a convenience sample selected to achieve a high response rate, which it achieved (81%), minimising non-response bias. The video lists provided by the YouTube API were not random samples but contained a wide range of types of video (including both popular and unpopular), except that older videos were avoided. There were substantial differences between categories in the average properties of the videos returned and the proportion of videos returned on multiple days. The most popular categories from the YouTube metadata collected based on average view counts are varied: From TV, Best of, Animation and How-to. Cause-based video categories tended to be unpopular. Video popularity did not seem to be affected by video duration, on average. Users are more likely to interact with (comment, like, dislike) videos that are useful or supporting in some way. Videos that are interacted with more are not always more popular, with subject content affecting this relationship. In addition, high view counts associated with fewer likes, dislikes and comments per view, suggesting that indicators of popularity may not attract new viewers. The most popular categories with survey respondents were slightly different, partly reflecting their educational background (e.g., Education videos), and there were some (stereotypical) gender differences in the most popular categories. Respondents rarely believed that they were influenced by a video’s popularity or evidence of other users’ reactions to it when deciding to watch the video. Instead, they were most likely to be influenced by content-related factors, such as a video’s title and thumbnail picture. Despite previous research showing that people can be influenced by the opinions and watching habits of others, respondents claimed to be little influenced by this. Nevertheless, they frequently reported watching videos posted to Facebook, possibly trusting the person that posted the video. Thus, despite extensive discussion of various forms of viral information spreading, content, rather than popularity, is king in YouTube, although online word-of-mouth sharing through trusted relationships is also important. The main limitations of this research are that the data used may not be representative of YouTube and all UK YouTube users overall, so the conclusions should be interpreted cautiously. 3 | P a g e Acknowledgements I would like to express my deepest thanks to my supervisor Professor Mike Thelwall for all of your support, help, guidance, ideas, time, patience and understanding throughout the whole process of getting this thesis completed. I feel very lucky to have had you as my supervisor and appreciate everything you have done. I would also like to thank the wonderful Steph who without all of your support, encouragement, understanding, friendship, love and endless faith in me I would never have gotten this far. In addition I would like to thank Erica, Neil and Rob for all of your support and for always being there for me. I would also like to thank all those individuals, the 81%, who kindly completed my questionnaire and provided me with a wealth of data for this thesis. Finally, I would like to thank those friends who have provided moral support, understanding and messages of encouragement throughout this process. 4 | P a g e Table of Contents Abstract ................................................................................................................................................... 3 Acknowledgements ................................................................................................................................. 4 List of Tables ......................................................................................................................................... 10 List of Figures ........................................................................................................................................ 12 1 Introduction .................................................................................................................................. 15 1.1 Thesis Focus .......................................................................................................................... 15 1.2 Research Questions .............................................................................................................. 16 1.3 Contribution .......................................................................................................................... 17 1.4 Thesis Structure .................................................................................................................... 17 2 Literature Review .......................................................................................................................... 18 2.1 Popularity .............................................................................................................................. 18 2.1.1 What is ‘Popularity’? ..................................................................................................... 18 2.1.2 Influencers..................................................................................................................... 19 2.1.3 Popularity as an Influencer ........................................................................................... 19 2.1.4 Cult Popularity............................................................................................................... 19 2.1.5 Herding Behaviour ........................................................................................................ 20 2.1.6 Information Cascades ................................................................................................... 20 2.1.7 Word-of-Mouth ............................................................................................................. 20 2.1.8 Diffusion Theory ............................................................................................................ 21 2.2 Online Activity ....................................................................................................................... 22 2.2.1 The Social Web .............................................................................................................. 22 2.2.2 Reasons for Online Sharing ........................................................................................... 23 2.2.3 Online Video Sharing and Virality ................................................................................. 23 2.2.4 Types and Measures of Online Video Popularity .......................................................... 24 2.2.5 Video Sharing and Online Social Networks ................................................................... 24 2.2.6 Video Sharing Platforms ................................................................................................ 26 2.2.7 Factors Influencing Online Video Popularity................................................................. 28 2.3 Finding and watching YouTube videos ................................................................................. 30 2.3.1 YouTube Video Search and Recommendations ............................................................ 30 2.3.2 YouTube Video Popularity ............................................................................................ 30 2.3.3 Sharing YouTube Videos ............................................................................................... 31 2.4 YouTube Culture ................................................................................................................... 32 5 | P a g e 2.4.1 User Demographics ....................................................................................................... 33 2.4.2 Social Networking ......................................................................................................... 34 2.4.3 Opinion,
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