CONTRADICTORY MEGATRENDS DRIVEN BY SOCIAL TECHNOLO-

GIES

Professor of Sociology

Yonsei University

Sociological Studies of Net-work

-Community Studies (60’s) Friendship Network, Community Power StructureDevelopment of SNA techniques (L. Freeman, Borgatti, Lincoln,

Burt . . .)

-Network of Corporate Gover-nance (ex: interlocking board of Di-rectors)

-Inter-organizational Rela-tions

-Social Movements -World System Theory (state

network)

Micro

Macro

Network Capitalism

Example; Structural Eff ect

A’s Parents B’s Parents

Student A Student B Student A Student B

A’s Parents B’s Parents

Open Network Closed Network

Probability of becoming a delinquent boy is higher in ( ) network.

Internet revives interest of 60’s

Sociological Issues; Social Impact of Internet Has the Internet increased, decreased

contact? More on line Friends? Long distance friends?

Has the Internet support emotional ties? Contact with Family and old friends

anonymity and invisibility Privacy Identity (Multiple selves) . . .

Yet, N increased from hundreds to millions.

Netville Experiment

Does Internet produce Power-dispersion or Power concentration? Decentralized communication net-

work replace centralized communica-tion, undermining the central power.

As more people are connected, cen-tralized network structure produce a “winner take it all” society.

Two contradictory predictions each with compelling evidences.

Macro Issues concerning Inequality

1. Network Army weakens centralized (state) power

Candlelight vigil against beef import

Synch on the Net

Orchestration without a conductor;People can make voice!!

Why Power dispersion?

Information Asymmetry produces Power With knowledge & information you can gain power.

Centralized Network Decentralized Network

Information Asymmetry is reduced due to social technology

Examples of Power dispersion

Minerva; information superhighway

Doctor-Patent Relations

Professor-Student Rela-tions

Mass media / new media

Network Theory of KnowledgeAfrican Sculpture Picasso’s Cubism

Anyone can create by mixing.Ex: creative commons

R&D vs. Open Innovation

기존의 혁신 모델 개방혁신 모델Any Connected Individual can create the value, without means of production.

Small world Networks; Path vs. Walk

Gene expression Network Food Web Power Grid

Romance of the Three Kingdoms Korean Pops Keyword Network New Testament Net-work

Power Concentration: Winner Take all Society

# of people affected by power failure caused by lightening

Frequency

104

105

106

10710

0

101

102

103

1984-1997

Power Law

Preferential attachment

Mathew Effect “the rich get richer”

Why? Network Externality!The value of a fax depends on the number of faxes inter-connected . . . Mobile phone, Facebook. . .

Increasing Return

Centralization of Web traffic Net-work

August, 2000May, 2000

Degree

Mean 13.76

Std Dev 18.26

Network Centralization = 51.37%

Degree

Mean 0.74

Std Dev 1.59

Network Centralization = 3.80%

Among top 100 sites

If Links create values, inequality increases!

Network Externality

Zipf Law

http://www.useit.com/alertbox/9704b.html

• Some core group are more connected than the rest on line

• a small set of webloggers account for a majority of the traffic in the weblog world

• as more journal issues came online, more of citations were to fewer journals and articles

Network Society may produce extreme inequality!!

Links, Friends, traffic, Citations. . . Are distributed with power law