Category Archives: Music Mashups

Anime Music Video (AMV): Data-visualization Methods for Video Remixes

Figure 1: Safety Dance https://www.youtube.com/watch?v=vElbh2Ox1dA

Editorial Note: This is the first entry on Remix Data by Eduardo de Moura, a researcher and scholar from São Paulo, Brazil who has been developing visualization methods under the guidance of Eduardo Navas at The School of Visual Arts and The Arts & Design Research Incubator (ADRI) in the College of Arts and Architecture, The Pennsylvania State University. This entry marks the evolution of remixdata.net in becoming an online resource and hyperhub on which ongoing collaboration and research  on remix studies will be shared with the online community. The research is conducted among individuals who are mutually interested in remix and data visualization in the arts, humanities and social sciences.

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I have been developing my Ph.D. thesis at the State University of Campinas (UNICAMP) since 2014. Currently, with the assistance of the São Paulo Research Foundation (FAPESP), I had the opportunity to improve my research under the supervision of Professor Eduardo Navas at The Pennsylvania State University, School of Visual Arts and the Arts & Design Research Incubator (ADRI). This text forms part of the research I conducted during my time at Penn State.  I thank Eduardo Navas, Graeme Sullivan, Director of the School of Visual Arts and Professor of Art Education, Andrew Schulz, Associate Dean for Research in the College of Arts and Architecture, Andrew Belser, Director of the Arts and Design Research Incubator and Professor of Movement, Voice and Acting, and Tara Caimi, Karen Keifer-Boyd, Marta Cabral, Christen Sperry-Garcia, Felix Rodriguez, Alvaro Jordan, Aaron Knochel, Mark Ballora, Joe Julian and Cynthia White for making my residency at University Park productive. The main points of this paper were presentation as a dialogue at ADRI on February 16, 2018.

The research I conducted is part of my thesis – Anime Music Video (AMV), multi and new literacies: The remix in Otaku culture – focuses on the audio-visual productions belonging to an online community whose objective is the elaboration, distribution and appreciation of Anime Music Videos (AMVs). In this article, I intend to provide a summary of this ongoing research.

Anime Music Video (AMV): remix and new literacies

Remixes based on video edition is part of youth cultures: it constitutes a new practice of multilingual and multimodal literacy that includes new values, new aesthetics and new ways to create and share meanings (LANKSHEAR, 2007; LANKSHEAR AND KNOBEL, 2011; NAVAS, 2012; 2013; 2015). For this reason, it is important to recognize the nature that defines the new ways in which young people construct and share meanings in the contemporary world to have a better understanding of how youth cultures establish, through new literate practices, their networks, sociability, aesthetics and professionalization processes.

The video Safety Dance (Figure 1) is an interest example of this New literacies that circulate within youth cultures; especially, between fans of Japanese pop culture. Safety Dance was edited by Shin, a well-known AMV editor, who had won the 2012 Viewer’s Choice Awards (VCA) for “Best Dance Video” and “Best Video That Made You Want to Watch the Anime” – VCA is an import price given by the AMV portal the.org to, as it says, “acknowledge the videos that stand out above and beyond the rest of the video crowd.”

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–Eduardo de Moura Almeida

Analysis of 30 YouTube Music Video Mashups

30MashGridWeb

Figure 1: Visualization of 30 Music Video mashups taken from YouTube. Mashups were uploaded between 2006 and 2011

I am currently finalizing research on 30 YouTube music video mashups, uploaded between 2006 and 2011. I started this research during the last days of my post-doctoral work at the University of Bergen in May of 2012. I was able to refocus on this project during 2015 thanks to the support of a Faculty Research Grant from The College of Arts and Architecture at The Pennsylvania State University. I thank them for their ongoing support. In what follows I will introduce the principles of this research project.

10PrelemViz

Figure 2: Preliminary Visualization of the first 10 of 30 music video mashups. The list includes from top-left to bottom-right: 1) Danger Mouse Encore (Grey Album, Jay-Z and Beatles), 2) Radiohead vs. Dave Brubeck,  3) 99 Problems with Buddy Holly, 4) Ray of Gob (Madonna vs. Sex Pistols) , 5) The Strokes vs. Christina Aguilera, 6) Eminem Featuring Aerosmith Sing On For The Dream Moment, 7) Blondie Vs. The Doors – Rapture Riders, 8) Boulevard Of Broken Songs – Green Day ; Oasis ft.Travis ; Eminem, 9) Sour Glass (Portishead vs. Blondie vs. Kanye West), 10) Weezer vs. Queen.
Color code: light-green = special effects or titles, blue = main-track/instrumental, yellow= lyrics/complementary track, red = footage of both videos combined.

During my postdoctoral research I worked on three case studies of YouTube video memes. I published my findings in the paper “Modular complexity and remix: the collapse of time and space into search” Based on the editing patterns that I noticed the YouTube video memes shared,  it became evident to me that a particular grammar and syntax was at play in the way people edited diverse forms of music video remixes; this grammar also appears to be linked to the way music mashups are produced and function, and for this reason, after I finished my research on the music-video memes, I decided to look further into video-music mashups. I chose 30 of the most popular mashups between 2006 and 2011.  Given that remix as a form of cultural production is closely linked to basic music remixes it is worth evaluating how meme patterns move across different genres that combine image and sound as a single form of expression. Music video mashups are good case studies for this reason.

To analyze the patterns of the memes more accurately, I realized that it was not enough to visualize a grid of the video footage as I had done for my previous research. I needed to see how the footage of different videos was edited as one to complement the actual music remix. Therefore, I developed a color-coding system to mark the video edits. I did the first 10 manually, by laying color over the video montage (Figure 2).

This process took too long and was not very accurate, so I developed a batching method in which I evaluate the frames that correspond with the original music videos and assign them a numbered sequence that can then be run to create a montage that matches the original video montage. I share the examples of the first three videos below.

1_DangMousMontWeb

Figure 3: “Danger Mouse Encore (Grey Album, Jay-Z and Beatles)” Grid-montage of music video mashup. Video available at http://www.youtube.com/watch?v=qFd1QvNPKmI

1_DngMsJayZColorWeb

Figure 4:  “Danger Mouse Encore (Grey Album, Jay-Z and Beatles)” Video color-coded pattern. Color code: yellow = special effects or titles, blue =  instrumental/main-track, green = lyrics/complementary track, red = footage of both videos combined–or hybrid video with special effects.

2_RadioBrubeckMontWeb

Figure 5: “Radiohead vs. Dave Brubeck” Grid-montage of music video mashup. This version is no longer available on YouTube, but an alternate remix can be found here: https://www.youtube.com/watch?v=0PQQPUb8Rl0

2_RhBrubkColorWeb

Figure 6:   “Radiohead vs. Dave BrubeckVideo color-coded pattern. Color code: yellow = special effects or titles, blue =  instrumental/main-track, green = lyrics/complementary track, red = footage of both videos combined–or hybrid video with special effects.

3_JayBuddyMontWeb

Figure 7: “99 Problems with Buddy Holly” Grid-montage of music video mashup. Video available at: https://www.youtube.com/watch?v=4bUAzC9wgkw

3_JayZWeezColorWeb

Figure 8:   “99 Problems with Buddy HollyVideo color-coded pattern. Color code: yellow = special effects or titles, blue =  instrumental/main-track, green = lyrics/complementary track, red = footage of both videos combined–or hybrid video with special effects.

Based on these three videos we can see that the approaches vary but nevertheless there are some similarities already evident. For one thing, there is a need to go back and forth between footage in order to reinforce the fact that the video is of a music mashup of two songs. The first two videos show some aspect of the video (red) that supports the aural experience of the sound mix colliding. This is also evident in my preliminary visualization of the first ten videos (figure 2). There is an exception of two videos (mashups 3 and 5), which don’t have any combined or hybrid footage (red), but only juxtapose material of the originating sources.  When listening to the actual music remix, it becomes evident that it is because of the way the two songs are mashed that the videos are edited with basic montage. In all of the videos I have analyzed thus far, the image appears to support as best it can the aural experience of the remix. The reasons behind this begs a detailed theoretical examination. It is my aim that my analysis will provide a good sense of how image and sound complement each other in music video mashups. I have looked at more recent mashups on YouTube since 2012, and find that the elements in the 30 videos I am analyzing are still at play. This may mean that certain aesthetic and expressive conventions of communication are already well in place among video and music remixers. In the future, I will be sharing more details of my findings on all 30 videos in a formal paper.