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Youtube's Popular Culture Ment Organization, Cultural Institution, Or the Like, Or :111 :11 User)

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Youtube's Popular Culture Ment Organization, Cultural Institution, Or the Like, Or :111 :11 User) CHAPTER THREE identity of the uploader (whether a traditional media CI III 'I small-to-medium enterprise or independent producer, a , YouTube's Popular Culture ment organization, cultural institution, or the like, or :111 :11 user). 3 Our concern with the appearance ofthese videos, wi 1('1 appear to come from and what they appear to be, is JI1ulival desire to understand how content might be perceived :111<11,1 within YouTube's ecology; by focusing on the appar('11 1 11,11 the content coded, the study does not discriminate, JiJl' I'X Accounting for Popularity between 'pure' user-created efforts and supposedly IISl'l I videos produced for viral marketing purposes or those st'i ~l' In this chapter we draw on a survey of some of YouTube's most by marketing campaigns. In practice, these are often ilidisl iII popular content to establish some baseline knowledge about able, and to some participants, the role they perform is 1111' :-1: the range of uses people are making of the site. Understanding Our survey concentrated on the most popular vid{'os \ what YouTube might be for, and moving beyond moral panics the time period of the study, partly because it hdpl'd 10 about young people, the destruction of existing media business, our sample, but also because we were trying to undn'sla lld copyright infringement, or the trivialities ofuser-created content, of the dominant patterns in popular uses of YouTulll'. WI requires contextualizing YouTube's content with everyday media through these patterns, in this chapter we attem pt to loql practices. Simply looking at content on YouTube doesn't give us 'YouTube-ness' of You Tube - its shared and parlit:lliar ('01 the whole picture, of course - YouTube videos circulate and are culture - while respecting its complexity and diversily. W made sense of on other websites; they are embedded in blogs, not only at the mix of content that moves through Ihl' l-l discussed in living rooms, and they are produced in rich every­ but at the particular patterns of relations between vid,'()s I day or professional contexts. But combining this knowledge with website and the organization of You Tube itself. an analysis of the way particular types of videos move through But understanding how popularity works on Yoululll' \'(', YouTube as a system allows us to identify some of the most sig­ more than simply identifying and describing whid"1 uf' till' ' nificant and interesting patterns in YouTube's popular culture. have been watched the most. Is the 'popular' simply a \lUI This content survey draws on a sample of videos from four degree - how popular a particular cultural product is, lilt'; of YouTube's categories of popularity - Most Viewed, Most by its reach or sales? Or is it a matter ofkind - the CIIII ilia I Favorited, Most Responded, Most Discussed. Across these catego­ that are loved intensely, or that are 'of the people'? l~v~ ' 11 ' ries, 4,320 videos were gathered by sampling from six days across YouTube itself, content is represented as being more () I " ,~ two weeks in each ofthree months of2007 (August, October, and ular according to a range ofdifferent measures, inciudillfU November).1 A coding system was developed to categorize these videos according to textual and extra-textual features, coding for most viewed, most respon.ded, most discussed, top rateel, 1I111,\''/n origin, uploader, genre, and themes.2 previously popular, and most active 4 This coding scheme involved two primary categories: the appar­ And it offers a range of different time periods: ent industrial origin of the video (whether it was user· created or the product of a traditional media company), and the apparent today, this week , this mon.th, an.d all time 38 I ..­ ~.. '" YouTube:$=Pi ,~,~. :.. ' 41 We concentrated on four of these categories of popularity _ this is not all they do. They are not representations of reality, but Most Viewed, Most Favorited, Most Responded, Most Discussed technologies of re-presentation. Because they communicate to - because we (correctly, as it turns out) hypothesized that compar­ the audience what counts as popular on YouTube, these metrics ing across them would give us a sense ofthe way different kinds of also take an active role in creating the reality ofwhat is popular on video content are made popular by audiences in different ways. YouTube: they are not only descriptive; they are also perforrnative. Each ofthese measures ofpopularity orders YouTube according Michel Callon (1998) makes the argument that economic theo­ to a different logic ofaudience engagement. While all ofthese meas­ ries of markets 'format' real markets by making them calculable, ures rely on quantitative assessments - they all count things - the and therefore affecting the choices of real actors who participate categories Most Responded, Most Discussed, and Most Favorited in those markets. This is not the same as saying that the 'dis­ provide a way to access measures ofattention other than those that courses' of markets 'socially construct' our choices; rather, our have predominated in the broadcast era. Whereas Most Viewed models and understandings ofmarkets function technologically, most closely resembles the aggregate measures of attention uti­ producing knowledge that can be used in practice, but only within lized by mainstream media industries as a way ofcounting 'eyeballs the constraints of the ways this knowledge is structured and pre­ in front ofthe screen,'s each ofthe other three measures provides sented. Much more modestly, the various measures of videos' some account ofpopularity based on activities that signal a degree popularity within YouTube function similarly: to a certain extent ofparticipation in the YouTube community - ifnothing else, all of they make calculable and measurable a simplified and atomized them require the user to have an account. The Most Favorited cat­ model of audience engagement - based on the raw frequencies egory aggregates the videos popular enough to be added to a user's of views, comments, response videos, and additions to users' profile, and Most Discussed aggregates the videos that generate the favorites. In turn, these metrics shape the character of the most most comments, whereas Most Responded records the videos that popular content; users can either deliberately attempt to produce viewers were most frequently prompted to post a video response content that will achieve mass attention according to the preset to, either by filming their own material or linking to another video criteria, or they can ignore them altogether (and receive attention in the system. Because it compares types of popular video content from dramatically smaller audiences). As with the mainstream across these measures of popularity, this content survey doesn't media interpretations of what YouTube is for, this produces a simply tell us what is 'on' YouTube. Each of these ways of identi­ feedback loop between the perceived uses of and value logics of fying YouTube's popular culture ends up constituting a different YouTube; and its 'actual' uses and meanings. version ofwhat YouTube is, and what it is for. Because we were looking at a sample ofthe most popularvideos, The Two YouTubes the results ofthis content survey are not simply a reflection ofthe collective tastes ofthe YouTube audience as a whole. The picture The constructions of YouTube discussed in the previous chap­ of what YouTube is and how it is used that emerges from the ter somewhat simplistically represent videos on the website as study is also partly shaped by the way popularity is measured, and coming either from inside established media practice6 or outside the way popular content is represented on the YouTube itself ofit.7 In doing so, YouTube is imagined as a space where these two Ofcourse, in some ways , the popularity metrics do just what we categories co-exist and collide, but do not really converge: where might think - they measure the relative popularity of individual familiar forms of mass media content will be encountered along­ videos over a given time period, according to various criteria. But side amateur oddities; where television, cinema, music videos, 4.2 ·-~J~~~i·:· r ~e~s;1?opu1ar Culture ----------~---- and advertising, appear next to bedroom, boardroom, or back-yard True to the 'Broadcast Yourself' promise of YouTube, the productions. This dichotomy between the 'user-created' and 'tradi­ survey of the most popular content looks to be weighted, just tional media' content is of course problematic for understanding slightly, in favor ofuser-created videos. Just over halfthe material, YouTube as a site of new convergences and mutations of these or 2,177 videos, were coded as coming from user-created sources categories, and so employing it analytically (as we have done) is an - content produced outside of the mainstream, broadcast, or oversimplifYing move. Nevertheless, it provides a useful organiz­ established media. A majority of these videos were vlogs (nearly ing framework within which to begin a large-scale content survey, 40 percent), the conversational form that is somewhat emblem­ and our baseline division of the content into the categories 'user­ atic of YouTube's user-created content. Other genres included created' or 'traditional media' produced some interesting results: user-created music videos (15 percent) - including fanvids, and anime music videos;8 live material (13 percent) - musical performances, sporting footage, and 'slice of life' footage; and Number of MOST MOST MOST MOST TOTAL informational content (10 percent) such as newscasts, video­ Videos FA VORl TED VIEWED DISCUSSED RESPONDED game reviews, and interviews. Scripted material (8 percent) such Traditional 511 717 276 -= 308 1812 as sketch comedy, animation, and machinima - animation made User-Created 466 277 751 683 2177 using video-game engines often created by capturing and edit­ Uncertain 103 86 53 89 331 . ing choreographed gameplay - all made up a small part of the Totals 1080 1080 1080 1080 4320 sample.
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