UNIVERSITÀ DEGLI STUDI DI PAVIA DIPARTIMENTI DI SCIENZE POLITICHE E SOCIALI, STUDI UMANISTICI, GIURISPRUDENZA, INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE, SCIENZE ECONOMICHE E AZIENDALI. CORSO DI LAUREA INTERDIPARTIMENTALE IN COMUNICAZIONE, INNOVAZIONE, MULTIMEDIALITÀ DON'T BELIEVE THE HYPE UN'ANALISI MACROECONOMICA ED ETICA SUI MODELLI DI BUSINESS E MAJOR DEL WEB, BIG DATA E DATA MINING Relatore: Chiar.mo Prof. Paolo Costa Correlatore: Chiar.mo Prof. Andrea Fumagalli Tesi di Laurea di Giovanni Rabuffetti 2 Don't believe the hype Structure of the analysis Web economics & business models Historical perspectives Vision through technology literature ● Economic History ● ● ● Web 2.0 Wikinomics ● Critical literature highlights Dot-com Web ● ● Big data Concrete issues 3 Don't believe the hype The key to the reading Geert Lovink "Don't believe the hype, part 17. 'Big data is a big deal. It will change the way you do things in the future, and how you make decisions'." - Geert Lovink (@glovink) July 16th, 2013 Geert Lovink Born 1959, Amsterdam. Research professor of interactive Media at the Hogeschool van Amsterdam, founder director of the Istitute of Network Cultures. Made an early effort in helping to shape the development of the Web. Discuss tech policies before they get to the establishment 4 Early Internet to Web 1.0 Pre-commercial Internet USA, origins of the Internet ● ● ● ● Cold War american communications ARPA 1958 / Paul Baran 1960 Military Internet project Decentered computer networks ● ● No private use until 1980s Purpose-built networks (NASA's SPAN, CSNET, BITNET, CYCLADES..) Key concepts ● ● ● ● Safe Fast Decentered Anti-bombing ● ● ● Tim Berners-Lee Enquire & Information sharing Hyper Text Markup Language 5 Early Internet to Web 1.0 Introducing commercial Internet ● ● ● ● ● Early 1990s programming of several browsers 1994, Canter & Siegel spam 1995, NSF stops commercial prohibition 19,6 million computers connected Growing interest from commercial realities Tim Berners-Lee, Weaving the Web “In 1992 interest towards the Web was shown by the academic world, in 1993 it was shown by the industrial world.” TIME Magazine, 1994 6 Early Internet to Web 1.0 Commercial Internet ● New applications for the Web Netscape, by Andreessen & Clark ● ● Usenet, email, remote content ● ● + user inventions (ex. webcam) ● User friendly concept & interface “Perpetual beta” approach 1995, Highest IPO in history Paul Baran, 1968 “Internet in the future will be similar to a warehouse: a place in which users will be able to find any product they can imagine” Optimism for the future Silicon Valley start-ups: ● Investments ● ● ● ● ● Webvan.com Pets.com SwapIt.com eBay.com Amazon.com Tesco Online 7 The Dot-Com Bubble ● ● ● Recession in the commercial era 1995 to 1999, growing investments & technologies “Get Big Fast” behaviour 2000 Downward trend and bubble burst Web 1.0 system flaws Case study eBay Flexible Decentralized No GBF policy ● Markets were not ready Unusable technologies (Amazon case) No company know-how Misunderstood market's needs ● Internet didn't “change everything” ● vs SwapIt.com Rigid Centralized GBF oriented ● ● 8 Dot-com Bubble to Web 2.0 Beyond the flaws ● Some companies succeeded TIME Magazine, 2006 (eBay, Amazon, Google, Del.icio.us, Wikipedia..) Customer orientation ● Towards interactivity ● Emerging 2.0 services ● Internet users got prepared Successful companies ● Minimized internal work ● Fostered user engagement ● Offered free services ● ● ● ● ● ● ● Del.icio.us, social bookmarking and folksonomy Wikipedia, encyclopedia descending from Nupedia Google, most popular free Web research Digg, user-driven news YouTube, “broadcast yourself” & user-generated content Facebook, world's most popular social network Blogging platforms 9 Web 2.0 The new economic model ● Free services ● User work/contribution ● User information/customization Establishment of successful platforms ● ● ● ● ● Tim O'Reilly's “Web 2.0 Meme Map”, 2005 Social recognition Standard marketing use Usability of platforms and technologies Huge data flow 2013: 2,5 billion active Internet users Illustrating Web 2.0 characteristics 10 Big Data Establishment of technologies & 2.0 corporate approach led to great user data flow on the Web Google, The Flu Case USA, 2009 ● Outbreak of a great flu ● Monitoring users' queries ● Time, place, frequency, keywords ● Comparison with infected areas ● Forecasting next infection areas in the brief term Today's data flow Google: 24 petabytes per day Facebook: ½ petabyte per day YouTube: 1+ h videos uploaded per second Twitter: 400 million posts per day Awareness of the Power of data ● Not only for public health ● (Decide.com, Car flaws..) Different from “Small Data” Big Data are heterogeneous 3Vs ● Volume ● Variety ● Velocity Desktop Laptop Tablet Smartphone 11 Web 2.0 & the Wikinomics approach ● ● ● ● User appreciation for a reviving technology The Goldcorp case, 1999 ● Experimenting open business ways ● Sharing information with expert community Participation from companies & users D. Tapscott & A.D. Williams's Wikinomics ● Revolution in company management ● Online community- based vision ● New production models / against hierarchy ● 4 Principles: Openness, Peering, Sharing, Acting globally User-generated content Led to new business visions Early Wikinomics-oriented companies ● ● ● ● ● ● MySpace Innocentive Flickr Wikipedia Second Life Youtube ● ● Google The Human Genome Project The Prosumer concept ● ● ● Consumer included in value creation processes Customer innovation Eye on online creative communities 12 Big Data Ethical and practical problems Web 2.0 is tipically apt to receive user data flow V. Mayer-Schonberger & K. Cukier's Big Data ● Power of data in History: Stasi control ● Personal data in Amazon, Google, Facebook, Twitter.. ● Anonymous data is not anonymous: the AOL case ● The NSA Case: 20 mln interactions spied, calls, emails, money transactions Probability of crimes: an emerging american case The economic model changes ● ● ● ● ● No more cash money requested Money is made upon user data 2.0 Web companies rely on free user data Information that's precious in many ways ● ● ● ● ● Memphis, Tennessee: experimental CRUSH Program Crime Reduction Using Statistical System Data recommends areas and time Towards recognizing people in advance Evolution of profiling technique Preventing crime / pre-commitment punishment 13 Problems of today's business model The work of being watched, Mark Andrejevic Early examples of exploitation of personal data ● 2000-01 The case of DotComGuy ● VCR TV Technology “While the viewer watched television, the box would watch the viewer” (Lewis, 2000) ● ● Panopticon company situation Consumption becomes productive ● Data changes mass market ● The TiVo case ● Web browser's cookie 14 Problems of today's business model Amorality of Web 2.0, according to Nicholas Carr The New Yorker, 1993 The spider's Web: ● ● Barbaro & Zeller's (NYTimes) inquiry on anonymous data, the Thelma Arnold/AOL case Tom Owad & Amazon wishlists, Yahoo! People Search, Google Maps Outcome problems “On the Internet, nobody knows you're a dog” ● ● ● Is the Web really emancipating for its own nature? Marketing techniques end up to be controlling, monitoring, influencing devices 2.0 user expressive services give companies oportunities to control and influence 15 Problems of today's business model Is Google making us stupid? Nicholas Carr, 2008 “The Internet is becoming a universal medium which activates very different forces, and it protends to newly transform american culture.” Geert Lovink, 2011 ● Cultural studies & the canon issue ● Against professionals ● Malfunctioning filter ● Major companies controlling access to culture 2.0 computing has a impact on culture ● Superficiality of blogosphere ● Google's tendency to transparent personalization ● Fragmented Web society ● Less average attention Outcome problems ● ● ● Web changes the way we think Controlling the Web / Controlling culture Influencers replace cultural critics Lovink: Stop trusting the web & start discussing technologies before they reach the establishment status 16 Concrete case analysis NSA & Web 2.0 majors, the power of controlled technologies 2013, NSA surveillance case ● ● Danger associated to governative control on Web's structures Bulk of sensible data on the Internet Glenn Greenwald on “The Guardian”, 2013 ● June 6th, 2013, the NSA is collecting user data through Verizon ● PRISM surveillance program ● Millions of customers spied ● Web traffic, call data, heterogeneous metadata ● Orders from Foreign Intelligence Surveillance Court ● Easily obtainable data ● ● ● ● ● ● ● Telephone calls: who/when Device geolocation: tracing movements IP Addresses: reveal used devices Email drafts: not legally protected Text messages: policies similar to emails' Cloud computing data: documents, photo and other Social media data: the new privacy frontier ● Continuation of previous orders The sub poena approach European Union ● Discovered international data monitoring ● ● Experienced political consequences Hypotesis of international data protection pacts 17 Concrete case analysis The Yahoo! case: exploitment of collective labor Yahoo! acquires Tumblr, 2013 Yahoo!'s acquisition history ● ● ● Marissa Mayer: “We promise not to screw it up” ● Spirit behind Yahoo!'s acquisitions ● ● ● Monitoring online communities Exploiting community labor / Replacing internal research Perceive, anticipate or pilot Web's tendencies 1999 acquired GeoCities Meant to control part of the total Web traffic & users 2005 acquired Flickr In order to have free access to professional and user-generated pictures 2005 acquired Del.icio.us Overview on a strongly indie internet community 2005 acquired Konfabulator Independent app-developing start-up Dangers of the business model ● ● Exploitment of free user labor Distruction of online communities