Course Overviewand Introduction

Networked LifeCSE 112

Spring 2004Prof. Michael Kearns

What do the following questions…

• How does Google find what you want?• How do tolerant populations become

segregated?• How did Hush Puppies make a comeback?• How many friends between you and Kevin

Bacon?• How should you split $10 with a stranger?• What can the Internet learn from Paris

subway?• How is file downloading like a competition?

…have in common?

An Emerging Science• Examining apparent similarities between many

human and technological systems & organizations

• Importance of network effects in such systems• How things are connected matters greatly• Structure, asymmetry and heterogeneity• Details of interaction matter greatly• The metaphor of viral spread• Qualitative and quantitative; can be very subtle• A revolution of

– measurement– theory– breadth of vision

Who’s Doing All This?

• Computer Scientists– Understand and design complex, distributed

networks– View “competitive” decentralized systems as

economies

• Social Scientists, Psychologists, Economists– Understand human behavior in “simple” settings– Revised views of economic rationality in humans– Theories and measurement of social networks

• Physicists and Mathematicians– Interest and methods in complex systems– Theories of macroscopic behavior (phase transitions)

• All parties are interacting and collaborating

Course Vision and Mission• A network-centric examination of a wide range of

social, technological, financial and political systems• Examined via the tools and metaphors of:

– Computer Science– Economics– Psychology and Sociology– Mathematics– Physics

• Emphasize the common themes• Develop a new way of examining the world

A Communal Experiment

• No similar undergraduate course• No formal technical prerequisites

– greatly aided by recent books– publications in Science, Nature, etc.– extensive web visualizations and demos

• A mix of humanities and science

Course Outline

The Networked Nature of Society(~1 lecture)

• Networks as a collection of pairwise relations• Examples of familiar and important networks

– Social networks– Content networks– Technological networks– Economic networks

• The distinction between structure and dynamics• Network formation

A network-centric overview of modern society.

Contagion, Tipping and Networks

(~2 lectures)

• Epidemic as metaphor• The three laws of Gladwell:

– Law of the Few (connectors in a network)– Stickiness (power of the message)– Power of Context

• The importance of psychology• Perceptions of others; interdependence and tipping• Paul Revere, Sesame Street, Broken Windows, the

Appeal of Smoking, and Suicide Epidemics

Informal case studies from social behavior and pop culture.

Introduction to Graph Theory(~1 lecture)

• Networks of vertices and edges• Graph properties:

– cliques, independent sets, connected components, cuts, spanning trees,…

– social interpretations and significance • Special graphs:

– bipartite, planar, weighted, directed, regular,…• Computational issues at a high level

Beginning to quantify our ideas about networks.

Social Network Theory(~4 lectures)

• Metrics of social importance in a network:– degrees, closeness, between-ness,…

• Local and long-distance connections• SNT “universals”

– small diameter– clustering– heavy-tailed distributions

• Network formation– random graph models– preferential attachment– affiliation networks

• Examples from society, technology and fantasy

A statistical application of graph theory to human organization.

The Web as Network(~2 lectures)

• Web structure and components• Web communities• Web search:

– hubs and authorities– the PageRank algorithm– redundancy and co-training

The algorithmic implications of network structure.

Emergence of Global from Local

(~2 lectures)

• Context, motivation and influence• The madness of crowds:

– thresholds and cascades– mathematical models of tipping– the market for lemons– private preferences and global segregation

Begin to connect to classical issues of human and societal behavior.

An Introduction to Game Theory(~2 lectures)

• Models of economic and strategic interaction• Notions of equilibrium

– Nash– correlated– cooperative– market– bargaining

• Multi-player games• Social choice theory

A powerful mathematical model of what happensover links in competitive and cooperative settings.

Social Games on Networks:Interdependent Security and Market Economies

(~2 lectures)

• Tragedies of the commons• Catastrophic events: you can only die once• Fire detectors, airline security, Arthur Anderson,…• Buying and selling on a network• Preferential attachment, price variation, and the

distribution of wealth

Blending network, behavior and dynamics.

Behavioral Economics(~2 lectures)

• What’s broken with game theory?• How should you split 10 dollars?• The return of context• Guilt and envy: fixing the theory

Controlled social psychology experimentsexamining how “rational” we really are(n’t).

Evolutionary Game Theory(~2 lectures)

• Fitness and evolutionary dynamics• Mimicking and replicating vs. optimizing• Evolutionary stable strategies• The evolution of cooperation• Replication and viral spread

From economics to biology, and back again

Internet Basics(~2 lectures)

• IP addresses• Routers• Domain Name Servers• ISPs• Congestion control, load balancing• The Web and URLs• Security issues, network vulnerability

Under the hood of the quintessentialmodern technological network.

Internet Economics(~2 lectures)

• Selfish routing• The Price of Anarchy• Peer-to-peer as competitive economy• Paris Metro Pricing for QoS• Economic views of network security

The collision of network, economics, algorithms, content, and society.

Modern Financial Markets(~2 lectures)

• Market microstructure– limit and market orders– order books and electronic crossing networks– network and connectivity issues

• Quantitative trading– VWAP trading, market making– limit order power laws

• Herd behavior and power law returns• Economic theory and financial markets• Behavioral economics and finance

A study of the network that runs the world.

Course Mechanics• Will make heavy use of course web page:

– www.cis.upenn.edu/~mkearns/teaching/NetworkedLife– You will need good Internet access!

• No technical prerequisites• Lectures:

– slides provided; emphasis on concepts– frequent demos, visualizations, and in-class experiments

• Readings: mixture of general audience writings and articles from the literature

• Three required texts:– “The Tipping Point”, Gladwell– “Six Degrees”, Watts– “Micromotives and Macrobehavior”, Schelling

• Problem sets (approximately 6); about 25% of grade– computer/web exercises– short essays– quantitative problems– collaboration is not permitted

• Midterm; about 25% of grade• Final exam; about 50% of grade• Recitations: optional but highly recommended

– Tuesday 5-6 in Towne 311– Wednesday 5-6 in Towne 313

First Assignment

• Due next lecture (Th 1/15)• Simple background questionnaire• Last-names exercise