Music on YouTube: User engagement with traditional, user-appropriated and derivative videos

We present the first study of YouTube's most popular content genre, music videos.Our analysis of popular music videos identified three main types and 12 subtypes.User-appropriated videos emerged as the most important new category of videos.Derivative music videos stirred the highest levels of engagement among music videos.We discuss a halo effect that may explain the popularity of user-appropriated videos. YouTube is the leading Internet video service and one of the most popular websites in 2014. Music videos hold top positions in different YouTube charts, but the music video types or engagement patterns with them have not been systematically studied. In this paper we present three studies that focus on YouTube music. We first show that music videos are the most popular content genre in YouTube. We then present a typology of traditional and user-generated music videos discovered in YouTube. It includes twelve subtypes of music videos under three main types: traditional, user-appropriated, and derivative. Last, we present findings on user engagement statistics that go beyond view, comment, and vote counts. These metrics show that while music videos gather more views, engagement differences with other content genres are miniscule. However, there are notable differences in engagement between different music video types. This is prominent between different artists on one hand, and between traditional and user-generated videos on the other. We synthesize these findings by discussing the importance of user-generated videos in YouTube's music ecosystem.

[1]  Lixin Gao,et al.  The impact of YouTube recommendation system on video views , 2010, IMC '10.

[2]  Masood Masoodian,et al.  MANAGEMENT AND USAGE OF LARGE PERSONAL MUSIC AND PHOTO COLLECTIONS , 2007 .

[3]  Jennifer L. Gibbs,et al.  Social Media as a Catalyst for Online Deliberation: When Does the Medium Matter? , 2011 .

[4]  Lawrence Lessig,et al.  Remix: Making Art and Commerce Thrive in the Hybrid Economy , 2008 .

[5]  Gitte Lindgaard,et al.  An exploration of relations between visual appeal, trustworthiness and perceived usability of homepages , 2011, TCHI.

[6]  Ria Verleur,et al.  Flaming on YouTube , 2010, Comput. Hum. Behav..

[7]  Marcelo Maia,et al.  Identifying user behavior in online social networks , 2008, SocialNets '08.

[8]  David W. McDonald,et al.  The organization of home media , 2011, TCHI.

[9]  John Hartley,et al.  YouTube, digital literacy and the growth of knowledge. , 2017 .

[10]  Mike Thelwall,et al.  Commenting on YouTube videos: From guatemalan rock to El Big Bang , 2012, J. Assoc. Inf. Sci. Technol..

[11]  Frank Nack,et al.  Broadcast yourself on YouTube: really? , 2008, HCC '08.

[12]  Zongpeng Li,et al.  Youtube traffic characterization: a view from the edge , 2007, IMC '07.

[13]  Niklas Carlsson,et al.  Server selection in large-scale video-on-demand systems , 2010, TOMCCAP.

[14]  Roger Wattenhofer,et al.  The YouTube Social Network , 2012, ICWSM.

[15]  Tom Broxton,et al.  Catching a Viral Video , 2010, ICDM Workshops.

[16]  Jessica Lingel.  Live music, social media and participatory metadata , 2010, ASIST.

[17]  Mark W. Newman,et al.  Listening in: practices surrounding iTunes music sharing , 2005, CHI.

[18]  Sabine Himmel.  Youtube Online Video And Participatory Culture , 2016 .

[19]  Donna Pendergast,et al.  An Investigation of Early Childhood Teacher Self-Efficacy Beliefs in the Teaching of Arts Education , 2011 .

[20]  Paul A. Cairns,et al.  Critical methods and user generated content: the iPhone on YouTube , 2009, CHI.

[21]  Bin Gu,et al.  Content Contribution in Social Media: The Case of YouTube , 2012, 2012 45th Hawaii International Conference on System Sciences.

[22]  Elizabeth A. Buie,et al.  Meditations on YouTube , 2013, DPPI.

[23]  David M. Pennock,et al.  Predicting consumer behavior with Web search , 2010, Proceedings of the National Academy of Sciences.

[24]  J. Seigne,et al.  YouTube as source of prostate cancer information. , 2010, Urology.

[25]  Flavio Figueiredo,et al.  The tube over time: characterizing popularity growth of youtube videos , 2011, WSDM '11.

[26]  Lassi A. Liikkanen.  Three Metrics for Measuring User Engagement with Online Media: Case Example YouTube , 2013, ArXiv.

[27]  Yuan Ding,et al.  Broadcast yourself: understanding YouTube uploaders , 2011, IMC '11.

[28]  Patrick Waelbroeck,et al.  An Economist's Guide to Digital Music , 2004, SSRN Electronic Journal.

[29]  Walter E. Hurst,et al.  Music and Recording , 1975 .

[30]  Nina Reeves,et al.  An ethnographic study of music information seeking: implications for the design of a music digital library , 2003, 2003 Joint Conference on Digital Libraries, 2003. Proceedings..

[31]  Pablo Rodriguez,et al.  I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system , 2007, IMC '07.

[32]  Stephen P. Lewis,et al.  The Scope of Nonsuicidal Self-Injury on YouTube , 2011, Pediatrics.

[33]  A. Strauss,et al.  Grounded theory , 2017 .

[34]  Jin Kim,et al.  The institutionalization of YouTube: From user-generated content to professionally generated content , 2012 .

[35]  Lassi A. Liikkanen,et al.  Shuffling Services: Current Trends in Interacting with Digital Music , 2016, Interact. Comput..

[36]  Jennifer Gibbs,et al.  Social media as a catalyst for online deliberation? Exploring the affordances of Facebook and YouTube for political expression , 2013, Comput. Hum. Behav..

[37]  Lassi A. Liikkanen.  Music interaction trends in Finland: YouTube and Spotify , 2014, MindTrek.

[38]  Paul M. Haridakis,et al.  Social Interaction and Co-Viewing With YouTube: Blending Mass Communication Reception and Social Connection , 2009 .

[39]  H. Mackay,et al.  Extending the Social Shaping of Technology Approach: Ideology and Appropriation , 1992 .

[40]  Lassi A Liikkanen.  Three Metrics for Measuring User Engagement with Online Media and a YouTube Case Study , 2013 .

[41]  Jiangchuan Liu,et al.  Understanding the Characteristics of Internet Short Video Sharing: YouTube as a Case Study , 2007, ArXiv.

[42]  Nuria Oliver,et al.  Looking at near-duplicate videos from a human-centric perspective , 2010, ACM Trans. Multim. Comput. Commun. Appl..

[43]  ชวิตรา ตันติมาลา.  Constructing Grounded Theory: A Practical Guide through Qualitative Analysis , 2017 .

[44]  Andreas Butz,et al.  Listening factors: a large-scale principal components analysis of long-term music listening histories , 2012, CHI.

[45]  J. Stephen Downie,et al.  Music information retrieval , 2005, Annu. Rev. Inf. Sci. Technol..

[46]  Mirjam Wattenhofer,et al.  YouTube around the world: geographic popularity of videos , 2012, WWW.

[47]  Igor D. D. Curcio,et al.  Video as memorabilia: user needs for collaborative automatic mobile video production , 2012, CHI.

[48]  Christopher Cayari.  The YouTube Effect: How YouTube Has Provided New Ways to Consume, Create, and Share Music , 2011 .

[49]  Antti Salovaara,et al.  : Helping in the legal use of open images , 2012, CHI 2012.

[50]  K. Charmaz,et al.  Constructing Grounded Theory: A practical guide through qualitative analysis Kathy Charmaz Constructing Grounded Theory: A practical guide through qualitative analysis Sage 224 £19.99 0761973532 0761973532 [Formula: see text]. , 2006, Nurse researcher.

[51]  Michael L. Nelson,et al.  Music Video Redundancy and Half-Life in YouTube , 2011, TPDL.

[52]  David M. Nichols,et al.  How people find videos , 2008, JCDL '08.