Webzing the economy
&
economizing the Web
4/4/2013
Michalis Vafopoulos
vafopoulos.org
Do you believe it?
That a mathematician made an online
call to solve important and difficult
mathematical problems by
coordinating many researchers
through the Web?
Public spending in Real time?
It is the economy, stupid!
How long takes to have 50 million users?
• 38 years for telephone
• 13 years for television
• 4 years for Internet
• 3 years for iPod
• 2 years for Facebook
• <1 year for Google +
• the next: Linked Data company???
5
Main issues
①Web economics & business
②Goods in the Web
③Users
④Consumption and Production in the Web
⑤The Web of Data emerging industry
⑥Student evaluation & how to work
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the Web Science perspective
① Internet economics: the predecessor
② Partial analysis of the Web economy
–
e.g. network economics, digital goods etc.
③ Mainly focus on business implications
④ Issues: Auctions, e-commerce, search engines
⑤ Lately, net neutrality & excessive market power
⑥ Web science perspective
– Standalone artifact
– How the Web transforms economy and business
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Web economics
• Introduction
• The Web Economy
–
–
–
–
–
– Economy after the Web
– Existing theories and
missing tools
• Goods in the Web
–
–
–
–
Information goods
Digital goods
Network goods
Web goods
Network Effects
Peer & non-market production
Market Structure
Antitrust regulation
Web-based development
• The Web Business
–
–
–
–
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E-commerce
Business models
Advertising & sponsored search
User behavior analysis
Goods in the Web
①Data, information, knowledge
②Information goods
③Knowledge goods
④Digital goods
⑤Web goods
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Information goods: definitions
Definition I
the good, which main market value emanates
from the information it contains.
Definition II
anything that can be digitized (Varian)
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Information goods: characteristics
•
•
•
•
•
•
high fixed cost of production
low marginal cost of reproduction
increasing returns to scale
experience good
public or a private good
non-rival and sometimes non-excludable
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Knowledge goods
exogenous or endogenous inputs in production as:
①know-what (facts)
②know-why (scientific knowledge)
③know-how (skills)
④know- who (networks)
1, 2 easily reproducible
3, 4 not easily reproducible
4 more important in the Web era
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Digital goods
Bits with economic value, which are (Quah):
①nonrival
②infinitely expansible
③(Initially) discrete or indivisible
④aspatial
⑤recombinant
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Externality
①analyzes the impact that individual decisionmaking has on the other agents
②comparison of how decision-making involves
others without exchange
③Positive (i.e. education) or
④Negative (i.e. profiling)
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Network externality
Network externality:
①Some goods/services create more value when
more users consume the same goods and
services
②They have little or even no value if they are
used in isolation (e.g. telephony)
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Network externalities in the Web
Source of externalities =linking
①Web 1.0: documents (demand)
②Web 2.0: Users (supply)
③Web 3.0: structured data (?)
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Network externalities in the Web
Linked Data
• bidirectional and massively processable
interconnections among online data
• enabler for existing infrastructures
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Network externalities in the Web
Negative:
• lack of trust
• security,
• identity theft
• clickjacking
• Spamndexing
• spoofing
• …
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The basics of
network modeling
You see a product…
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And some reviews
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And some recommendations…
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The Amazon co-purchasing network
Item X co-purchased
most frequently
with products Y1, Y2,..
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Amazon: the book-based multi-store
The Amazon copurchase network
for all item
categories
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hidden complementarity saves MS
MS (purple) & Apple
(orange) communities
are “mediated” by
compatibility like
VMware Fusion,
Parallels Desktop and
compatible products
like Office for Mac.
Triad analysis: Winners in Product wars
Analysis shows that copurchase links not only
manifest complementary
consumption, but also
reveal competitive
relations among products
that are perfect
substitutes.
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Switching to best sellers
the case of Internet security market
Ass: if products A, B &
C are perfect
substitutes (authority
triad), then A has
higher sales rank
consumers who bought
Internet security s/w,
more often, also bought
Norton Internet Security
than related products
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Paychecks…
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b
a
n
k
r
u
p
t
c
y
…
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Why networks?
• To be self-contained (actor)—and to be thoroughly
dependent (network)—is to say twice the same thing.
(Actor-Network theory)
• Easy to model and visualize relations
• Easy to calculate major statistics
• The study of the Web network help us to conclude
that most of real networks are:
– Self-similar (Scale-free)
– Small worlds
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Network theory and related fields
Web
Science
Financial
Network
Analysis
Social Network
Analysis
NETWORK
THEORY
Computer
Science
Graph & Matrix
Theory
Biological
Network
Analysis
Initial source Soramaki
how?
• Define:
1. Node (e.g. person, business)
2. Link [directed or not] (e.g. friendship, commerce)
And if necessary:
3. Evaluation of node (e.g. score, potential)
4. Evaluation of link (weight)
4
0.54
(e.g. trust)
5
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Web Goods: definition
Existing approaches fail to both capture the
digital and the network dimension (aka
virtualization)
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Web Goods: definition
sequences of binary digits that
• are identified and communicated by an
exclusively assigned URI and
• affect the utility of or the payoff to some
individual in the economy.
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Web Goods
Their market value stems from the digital
information they are composed from and a
specific part of it, the hyperlinks, which connect
resources and facilitate navigation and editing
over a network of Web Goods with minimum
cost.
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Web Goods: categories
• Pure: basically exchanged and consumed
in the Web and are not tightly connected
to an ordinary good or a service (pre-)
existing in the physical world.
• Non pure (e.g. car’s photo in the Web)
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Web Goods: categories
• commercial (e.g. sponsored search results)
• non-commercial (e.g. Wikipedia entries)
----
• public (e.g. Linked Open Data)
• private (e.g. subscription to online magazine)
– financial fee
– “personal data” fee
– “social” or “membership” fee
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Web economy
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Consumption in the Web
• More energetic and connected consumption
– search and review, collaborative filtering
– what connected consumers create is not simply
content (e.g. product reviews) but context.
• Consumer coordination at large in the Web:
the Amazon co-purchase network
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Consumption in the Web
• Personal data abuse and regulation challenges
• Joint consumption of information and
advertisements in massive scale
• Moving the borders between production and
consumption
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Moving the borders between production
and consumption
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Production in the Web
① Inputs: information and knowledge reloaded
② Incentives: from property to commons
③ Peer Production: decentralized inter-creativity
outside the classic market
④ From mass to networked media
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Incentives: from property to commons
Property rights can be further analyzed to 4 parts:
i. The right to use economic resources.
ii. The right to modify form and substance of resources.
iii. The right to benefit from use of resources.
iv. The right to transfer resources.
• Traditional economy: 1st consumers, the rest producers
• Web?
• the 4th P: Property, Procurement, Patronage and Peer
Production (commons)
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Web business
①IT vs. Web economy
②Google model
o The Sponsored-search market
o Who’s the data?
③App vs. Web economy
o patent’s war
o Apple: the digital zombie
o HTML5 effect
④ The Web of Data emerging industry
⑤ Discovering the market sentiment in the Web
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Types of network externalities
①Direct (e.g. mobile phones)
②Indirect (e.g. mobile phone accessories)
③Two-sided network effects (or multi-sided
platforms) (e.g. hardware-software platforms and
the Google’s advertising platform)
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Issues in network markets
Network monopoly (e.g. Microsoft, Google)
Possible regulatory policies:
①Divestiture of the monopoly into separate firms.
②Unbundling or wholesale access to incumbent’s
facilities (e.g. Internet explorer).
③Licensing of proprietary interfaces to
potentially competing platforms.
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Web Goods vs. Digital Goods
• restricts non-rivalry and infinite
expansibility (concurrency capacity)
• initially discrete and indivisible, but
• Web 2.0: micro-chunks consumption
• easily edit, interconnect, aggregate and
comment
• extends aspatiality and atemporality from
local (e.g. personal HD) to global level (e.g.
downloadable file link)
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Web Goods as commodities
information and knowledge:
multiple and controversial definitions
Web Goods: qualify as commodities (Debreu, 1959)
• stable identity (URI)
• completely specified physically
• temporally and spatially (reside physically in
a Web server during a specific period of time)
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Consumption & Production in the Web
Existing literature: the Web will lower prices because:
① lower search and fixed costs
② less product differentiation (e.g. location is less
important)
③ “frictionless commerce”
Actually: no much evidence
The real transformation:
More choices with less transaction costs in production
and consumption.
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information and knowledge reloaded
the production of information is based on 3 inputs:
(a) existing information
(b) the mechanical means of conceiving, processing and
communicating information and
(c) the human communicative capacity (geography still
matters in some sectors)
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Peer Production: decentralized intercreativity outside the classic market
① virtuous cycle : productivity creates new knowledge,
attracts new Users, increase productivity, creates
new knowledge...
② A peer’s private productivity < his social productivity
due to supply-side knowledge externalities.
③ Peer Production happens if Users do not take
advantage of other’s knowledge sharing (free riding),
but contribute to the total productivity of the
community.
④ usually fails due to lack of critical mass of Editors and
in cases where sharing costs are higher than the cost
of atomization.
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From mass to networked media
① de-massification of the media as a result of
information overload and technological advancements
(Toffler)
② In the mass media the profit-maximizing strategy is to
attract attention and not to invest in production
quality.
③ Networked media: Never before was possible to
create, distribute, promote yourself and get feedback
for your music, writings or any other online content
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Projects
Web Goods characteristics
Compare with traditional good categories
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What about the mathematician?
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supplement
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Main issue
Identify purchasing patterns in Web retail
using available public data
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outline
① Before analysis
② Data
③ Innovations
④ Main results
⑤The Amazon co-purchasing network
⑥Amazon: the book-based multi-store
⑦Triad analysis: Winners in Product wars
⑧Switching to best sellers
⑨Hidden complementarity saves MS
59
Before analysis
 Why Amazon? the best proxy for Web retail
 Algorithms: item-based top-N recommendations
 Analysis? co-purchase directed graph
 related literature?
 Computer science (Collaborative filters, Karypis)
 Economics (market basket analysis, Oestreicher-Singer)
 Software? Gephi, iGraph, FANMOD, mysql, & xls (old
habits!)
Data
 226,238 items
 13,351,147 co-purchase connections
 The crawler was started with an initial set of 300
items, which were the top 10 selling products in each
of the thirty categories.
 61 recommendations per item (average)
 2nd level added 17,204 items
 3rd 208,740 items
Innovations
 Cross-category analysis
 Broad graph (in dyads at least one from category)
 Strict (both items from the same category)
 All recommended items crawled (max 104)
 Triads analysis
 Community analysis
Main results
 Amazon has evolved into a book-based multi-store with
strong cross-category connections.
 Top selling products are important in the co-purchase
network, acting as hubs, authorities & brokers.
 Co-purchase links not only manifest complementary
consumption, but also switching among competitive
products (e.g. Kaspersky -> Norton).
 competitive products consumed as complements
because of the existence of compatibility and
compatible products that facilitate their joint
consumption.
overview
①Amazon: the book-based multi-store
②Triad analysis: Winners in Product wars
③Switching to best sellers
④Hidden complementarity saves MS
Questions?
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Descriptive statistics
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Amazon: the book-based multi-store
Figure shows the interconnections among all
different categories of products in the Amazon
co-purchase network.
A link from category A to category B is added if
products from category B are present in the
broad network of category A.
The link intensity grows with the number of
products that are present in that network and
the size of a category denotes the number of
products that belong to it.
The stronger links are from Movies & TV to
Books, from Kitchen & Dining to Books, from
Toys & Games to Books and from Books back to
Movies & TV.
The Amazon copurchase network
for all item
categories
66
hidden complementarity saves MS
Fig. 2 shows a part of the Strict software co-purchase
network, where different colors indicate different
community membership. Different product communities
have been identified based on the spin glass community
detection algorithm and has been computed by the R
package iGraph. It is interesting to observe that
seemingly competitive products of Apple and Microsoft
are in reality consumed as if they were complementary.
Microsoft (nodes with red color) and Apple (nodes with
blue color) product communities are “mediated” by
compatibility like VMware Fusion, Parallels Desktop and
compatible products like Office for Mac.