Transcript cim.unipv.it

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
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Don't believe the hype
Structure of the analysis
Web economics & business models
Historical perspectives
Vision through technology literature
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Economic History
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Web 2.0
Wikinomics
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Critical literature
highlights
Dot-com Web
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Big data
Concrete issues
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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
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Early Internet to Web 1.0
Pre-commercial Internet
USA, origins of the Internet
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Cold War american communications
ARPA 1958 / Paul Baran 1960
Military Internet project
Decentered computer networks
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No private use until 1980s
Purpose-built networks
(NASA's SPAN, CSNET, BITNET,
CYCLADES..)
Key
concepts
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Safe
Fast
Decentered
Anti-bombing
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Tim Berners-Lee
Enquire & Information sharing
Hyper Text Markup Language
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Early Internet to Web 1.0
Introducing commercial Internet
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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
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Early Internet to Web 1.0
Commercial Internet
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New applications for
the Web
Netscape, by Andreessen & Clark
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Usenet, email,
remote content
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+ user inventions
(ex. webcam)
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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:
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Investments
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Webvan.com
Pets.com
SwapIt.com
eBay.com
Amazon.com
Tesco Online
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The Dot-Com Bubble
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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
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Markets were not ready
Unusable technologies (Amazon case)
No company know-how
Misunderstood market's needs
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Internet didn't “change everything”
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vs SwapIt.com
Rigid
Centralized
GBF oriented
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Dot-com Bubble to Web 2.0
Beyond the flaws
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Some companies
succeeded
TIME Magazine, 2006
(eBay, Amazon,
Google, Del.icio.us,
Wikipedia..)
Customer
orientation
● Towards
interactivity
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Emerging 2.0 services
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Internet users got
prepared
Successful companies
● Minimized internal work
● Fostered user engagement
● Offered free services
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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
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Web 2.0
The new
economic model
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Free services
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User work/contribution
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User
information/customization
Establishment of successful platforms
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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
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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
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(Decide.com,
Car flaws..)
Different from “Small
Data”
Big Data are
heterogeneous
3Vs
● Volume
● Variety
● Velocity
Desktop
Laptop
Tablet
Smartphone
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Web 2.0 & the Wikinomics approach
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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
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MySpace
Innocentive
Flickr
Wikipedia
Second Life
Youtube
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Google
The Human
Genome
Project
The Prosumer concept
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Consumer included in
value creation
processes
Customer innovation
Eye on online creative
communities
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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
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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
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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
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Problems of today's business model
The work of being watched, Mark Andrejevic
Early examples of
exploitation of personal
data
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2000-01
The case of
DotComGuy
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VCR TV Technology
“While the viewer watched television, the
box would watch the viewer” (Lewis,
2000)
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Panopticon company situation
Consumption becomes
productive
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Data changes mass market
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The TiVo case
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Web browser's cookie
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Problems of today's business model
Amorality of Web 2.0, according to Nicholas Carr
The New Yorker, 1993
The spider's Web:
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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”
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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
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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
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Superficiality of blogosphere
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Google's tendency to
transparent personalization
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Fragmented Web society
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Less average attention
Outcome problems
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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
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Concrete case analysis
NSA & Web 2.0 majors, the power of controlled technologies
2013, NSA surveillance
case
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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
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Easily obtainable data
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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
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Continuation of previous orders
The sub poena approach
European Union
● Discovered international data
monitoring
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Experienced political consequences
Hypotesis of international data
protection pacts
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Concrete case analysis
The Yahoo! case: exploitment of collective labor
Yahoo! acquires Tumblr, 2013
Yahoo!'s acquisition history
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Marissa Mayer:
“We promise not to screw it up”
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Spirit behind Yahoo!'s acquisitions
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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
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Exploitment of free user labor
Distruction of online
communities