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Long tail big data


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Long tail big data

  1. 1. Long Tail, Big Data:On-Demand Culture andMedia SpectatorshipChuck TryonMay 12, 2013UniversitàCattolica del SacroCuore
  2. 2. On-Demand CultureChris Anderson : no physicalbarriers to media distribution(The Long Tail)David Bordwell: “films havebecome files” (Pandora’s DigitalBox).More people watch films viaInternet than on physicalmedia (DVDs, Blu-Rays)“Promise that media textscirculate faster, more cheaply,and more broadly than everbefore.” But at what price?Ira Deutchman: distribution ascentral problem of movieindustry today
  3. 3. Platform MobilityPlatform mobility—“far more than the mere technologicalchanges that allow mobile access. It also includes thesocial, political, and economic changes that makemobile access more desirable.”A question of how screens, texts, and viewers movethrough space and time (encompasses limits to mobilityas well)
  4. 4. Mobile SpectatorshipImagines anactive, engaged, butindividualized viewerMove from Lynn Spigel(“Make Room for TV”) toplatform mobility (“MakeAny Room Your TVRoom”)Often sold as a means ofpromoting “familyharmony” throughpersonal viewing
  5. 5. New DistributionModels/LogicsNational Association of Theater Owners: by the end of 2013, movies nolonger distributed on celluloid3D as “Trojan Horse” that supported conversionSocial media (Twitter, Facebook) open up new modes of engagement, butalso allow studios to measure audience interest and create participatoryactivities to involve audiences in the “work” of marketing films“Sentiment mining”Crowdsourcing and crowdfunding through KickstarterUnlimited storage space makes “shelf space” irrelevant: The Long TailBut this does not eliminate production or promotion costsNew models that alter the distribution “windows” in which films and TVseries are made available.In some cases festivals (SXSW, Sundance, Tribeca) deliver films via VOD
  6. 6. On-Demand Spectatorship:Major U.S. PlayersSubscription Video onDemand (SVOD):Netflix, HuluPlus, AmazonPrime, Warner ArchiveInstant, Redbox InstantTransactional Video onDemand (TVOD):Amazon, Vudu, YouTubeAd-supported(ADVOD):Hulu, SnagFilms, CrackleDownload to Own:iTunes, Vudu, UltraViolet
  7. 7. Big Data“The ability of society to harness information in novel ways toproduce useful insights or goods and services of significantvalue” (2).Role of Google Search terms in tracking the movement ofH1N1 Virus, Amazon Recommendations in making bookbuying predictableBig data works by taking “huge quantities of data in order toinfer probabilities” (12).Not interested in why something is happening; insteadfocused on documenting what is happening (correlations, notcausation)Predictive analytics: “widely used in business to foreseeevents before they happen” (58).Big Data: A Revolution that Will Transform How We Live,Work, and Think, Viktor Mayer-Schonberger and KennethCukier (2013).
  8. 8. House of Cards: BingeViewingProduced by David Fincher(The Social Network, FightClub), starred Kevin SpaceyCalculated to attract reviewsfrom tastemakers infilm, tech pressReported $60 million budget for13 episodesNot the first example of SVODoriginal programming (Hulu’sDay in the Life)All episodes releasedsimultaneously on February1, 2013Defies traditional distributionmodels based on scarcity
  9. 9. House of Cards and BigDataAudience behavior can bemeasured, calculated, predicted, commodified (also used byAmazon and other retailers)Netflix knowswhen, where, what youwatch, when you pause or fast-forwardNetflix records “hundreds ofmillions” of events on a dailybasisCollective screenings andshared accounts introduceBig Data challenge forrecommendation algorithmAllows Netflix to market directlyto consumers rather than payingfor expensive TV advertising
  10. 10. Big Data and ProductionPotentially allows studios to calculate whatnarrative techniques should be included in agiven film or TV showWorldwide Motion Picture Group: use of dataanalysis to assess script marketabilityPotentially arbitrary: Company has calculatedthat movies with scenes in bowling alleys lesslikely to be profitableSimilar model with Amazon Pilots: 14 originalTV series and audience votes on which will getproduced
  11. 11. Mobile/MonitoredSpectatorshipNew media technologies “provide the media andculture industries with the means of surveillanceand control” (Bolin 2012).Mark Andrejevic: “monitored mobility”Andrew Leonard, Big data turnsaudiences into “puppets” (February 1, 2013).But these models fail to account for non-monitoredactivities, as well as attempts by fans andindependent producers to use data for alternativemodes of distributionReintroduces but complicates classic juxtapositionbetween active viewers and passive audiences…
  12. 12. From Audiences toCrowds…On-Demand Moviescreenings:Gathr, Tugg, Rain (Brazil)Girl Rising: generated100,000 reservedticketsStar-driven featureabout girls’ experiencesacross the globeCrowdsourcing:Wreckamovie, Snakes ona Plane, socialmedia, Amazon pilotsCrowdfunding:Kickstarter, IndieGogo.
  13. 13. Kickstarter andCrowdfundingAllows “long tail” creators to solicit funds for a creative project (movie, webseries, music, games, software) onlineContinuation of older practices: we are accustomed to paying for films before seeingthemCurrently available only in the US and UKMost projects raise less than $10,000 US (see chart below)Film and music by far the most common projects
  14. 14. Kickstarter andDocumentaryThree of the best-reviewed films of 2012used KickstarterRecent Sundancefavorites: AmericanPromise, CitizenKoch, etc.Allowed filmmakers toleverage existing socialnetworks (social capital)built around causesIndie filmmakers use datato target potentialsupporters (andaudiences)
  15. 15. Kickstarter and“Independence”Romanticized ideal ofthe independent artistpitching her passionprojectMore recently, boundarybetween studio andindependent has beenblurredPaul Schrader, TheCanyonsRob Thomas/WB,Veronica MarsZach Braff, Wish YouWere Here
  16. 16. On-Demand SpectatorshipActive, mobile, individualized viewers whoblog, tweet, remix, and share moviesContent can be accessed on multiple devicesand viewed on-the-goMonitored audience that is renderedreadable, analyzable, and predictable throughBig DataThis “freedom” thus enables the very conditionof monitored mobility
  17. 17. Questions or Comments?Chuck Tryon, Fayetteville State Universityctryon@uncfsu.edu!