NBA 600: Session 23Large Networks

15 April 2003

Daniel Huttenlocher

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Large Networks

Networks underlying many aspects of both technological and social systems– Relationships: suppliers, customers, personal– Connectivity: supply chains, information

systems, online payment and delivery

Networks have some properties that are very different from “collections”– E.g., bell curve or normal distribution

• Height, weight, grades• Not incomes!

– Networks generally follow different distribution known as power law

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Network Effects

Metcalfe’s law– Value of network proportional to square of its

number of users – n2

• Value to each user is (proportional to) n• Times n users

Physical and electronic networks– E.g., phone system

• Value proportional to number of people reachable by phone

– Communication networks in general– Tendency towards single provider or standard

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Network Market Characteristics

Single vendor/provider– Long distance (pre ATT breakup)– ATT connected their own local exchanges

• Enough local share to dominate long distance and lead to further aggregation

Interoperability among vendors/providers– Standards

• Internet has many providers all using common hardware and software standards

– Licensing• CD’s have many vendors all licensing common

standard from Philips

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Example: Web Browsers

Substantial network effects– Easier for site developers to have one browser

or rock solid standard• Complex and (was) rapidly changing

True standards difficult to develop and maintain

Microsoft realized this and didn’t want to be the marginalized platform– In addition to bundling IE with the OS worked

hard to be compatible with market leader• IE 4 produced pages more similar to Netscape 3

than Netscape 4 did

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Networks and Lock In

Particularly high switching costs for products/services with network effects– Value of alternative lower until many users

• Decade-long transitions to new kinds of media E.g., vinyl to cassette to CD

• Difficulty for non-Microsoft Office software

Antitrust concerns specifically address network effects and resulting lock-in– E.g., AOL barred from upgrades to instant

messenger service unless interoperate with competitors

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Tipping Points

Malcolm Gladwell’s book Sudden changes that result from

seemingly small differences– Crime rates and policing– Epidemics of disease– Dominance of VHS over Betamax

Often underlying networks can provide some insight– Connections between people in spread of

disease, ideas, behaviors

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Dominant Player or Standard

Chances of tipping

Low High

Low LOW UNCLEAR

High LOW HIGH(telecom)

Economies of Scale

NetworkEffects

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Example: Network Effects and IM

In 1999 AOL had near 100% of instant messenger market– With AIM and ICQ combined

In AOL Time Warner merger FCC prohibited advanced IM services such as video– Unless AOL opened up its services to

interoperate with other providers

AOL now about 48% of market, petitioning FCC to drop restriction– Claim no longer risk of “tipping”– MSN (29%) and Yahoo (23%) have added

advanced services such as video

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Causing Positive Feedback

One strategy: inter-operability, standards– Ease of consumer adoption– Multiple competitors working together, though

not necessarily anyone– Potentially give up some performance– Backward compatibility (e.g., dual band phones)

A different strategy: going it alone– A “10x” product (Andy Grove)

• Much better than alternatives to help get over switching cost hurdle

– E.g., video game manufacturers

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Going It Alone is Hard

Need a major advance– But not enough by itself

Customers are “creatures of habit”– Difficult just to learn about new thing, or which

option is best• Easier if one clear widely supported choice

Importance of knowledgeable friends or acquaintances– Trusted help making decisions

Video game industry has built-in turnover– Under 20 yr olds major fraction of market

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Openness vs. Control

How much added value overall and share you can capture

Value added depends on– Product itself– Size of network

Your share depends on– Ability to capture the value– How open

• Resulting degree of competition

– Alliance vs. full openness

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US Digital Mobile Phone Networks

Compatibility at level of voice calls– Largest network effect: ability to reach anyone

Incompatibility at nearly every other level– Using phones on other carriers’ networks– Keeping phone number across carriers

• Legislation slowly being adopted

– Sending text messages across networks

Increases switching costs– While maintaining network effect

• Except for text messaging

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Content Distribution Media

Wide licensing/sharing of technology has proven successful strategy– VHS widely licensed vs. Beta “go it alone”– Music CD widely licensed

• Developed by Philips and Sony

– DVD widely licensed• Developed by consortium

Proprietary formats such as Sony mini disc less widely adopted– Intended as replacement for audio cassette

• Never reached that level of market penetration

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Network Effects: No Guarantees

Customers value larger networks– How much depends on product/service

Expectations of who will win critical Tradeoff of openness vs. control Various strategies

– Standards• Still leaving room for innovation/competition

– Highly similar incompatible technologies• US digital cellular networks

– Proprietary technologies• Consortium – more control than with standards• Going it alone – high risk/reward

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Network Structures

Regular networks– Slow, thorough information spread– Engineered

Small world networks– Fast, thorough information spread– Social

Random networks– Fast, sporadic information spread– Arbitrary (doesn’t happen much)

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Small World Networks

Arise in wide range of social contexts– Original experiment: forwarding letters to a

recipient in distant city, with no address

The Internet has a small worlds structure– Some long-distance connections, many local

ones• Not regular structure like phone networks

– Created by independent agreements among many entities – “social process”

Links between Web pages also have this kind of structure

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Properties of Small World Networks

Hubs and authorities– Hubs: elements of network that know about

many others• List keepers

– Authorities: elements of network “trusted by” or “referred to” by many others• Knowledge sources

Exploiting small world networks involves identifying hubs and authorities– Spreading information from the hubs– Enrolling the authorities

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Some Small World Networks

Web– Authorities: news sites, blogs, product sites,

reviews, etc.– Hubs: homepages, link pages, search engines

File sharing– Authorities: those sharing many files– Hubs: lists of where content can be found

Computer help– Authorities: experts about systems (you use)– Hubs: people who know who (you should) ask

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Growth of Small World Networks

IM has grown to 41M home users– Started with teens and pre-teens– Spread along social networks

• Groups that knew/saw each other regularly

– Lower density of “long distance” connections

Became accepted as new communications medium– Being adopted in corporate sector– Planned or deployed in digital cellular services

Internet grew in similar manner– But started at/between universities

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Marketing Microsoft’s 3 Degrees

Trying to create small world network demand– Software for community building

• Bringing IM and file sharing together

– Involvement of students in design and testing– Addressing legal issues of copyrighted content

Trust and reputation– Support for “vouching for friends”, “who to

trust”

Eventual goal broad collaboration tool that goes well beyond IM or Net Meeting

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Power Laws

Linear relationship on log-log plot– E.g., number of people vs. wealth

10

100

1,000

10,000

100,000

1,000,000

10,000,000

Assets $000’s20 400 8,000 1.28B

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Normal or Bell-Shaped Curve

Power laws fundamentally different from normal or bell-curve distribution– Normal: most people clustered around mean

• Small number of “outliers” above and below• Height, weight, etc.

Not 10 1000 meter tall people and millions of 1-2 meter tall people

Properties of individuals are often normally distributed

Properties of natural networks often follow power law distributions

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Small World Connectivity

Power laws are common– Very small number of elements that have an

extremely large number of connections and vice versa

– Exponential differences• Linear on logarithmic scales

Connectivity among Internet routers– Various research projects demonstrate power

law relationship• Number of routers vs. number of connections to

other routers Certain “key” routers very highly connected

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Exploiting Small World Networks

Identify the small number of participants that have vast resources/connectivity/etc.– They can be worth spending much more effort

marketing to• Because of what they can spend or do• Because of impact that they can have on others

Identify and incent hubs and authorities– Incentives for authorities to learn, like and

recommend your product– Incentives for hubs to refer to positive

authorities

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Web Reflects Social Networks

Links among people and communities– Web links follow social interaction patterns

Success of Google AdWords– Google is a way to find social networks

• Known for high quality of search results

– AdWords are paid links separate from search results• Google wants high quality ad results also

Rank more effective ads higher, not just fee based Based on cost-per-click * click-through-rate

• Advertiser bids maximum cost-per-click