Course Overview and Introduction Networked Life CSE 112 Spring 2004 Prof. Michael Kearns.

Slides:



Advertisements
Similar presentations
Six degrees: The science of a connected age By Duncan J. Watts Brian Lewis INF 385Q December 1, 2005 Brian Lewis INF 385Q December 1, 2005.
Advertisements

1 Small Worlds and Phase Transition in Agent Based Models with Binary Choices. Denis Phan ENST de Bretagne, Département Économie et Sciences Humaines &
Scale Free Networks.
Complex Networks Luis Miguel Varela COST meeting, Lisbon March 27 th 2013.
Course Introduction and Overview Networked Life CSE 112 Spring 2006 Prof. Michael Kearns.
Models of Network Formation Networked Life NETS 112 Fall 2013 Prof. Michael Kearns.
Course Introduction and Overview Networked Life Market and Social Systems Engineering (MKSE) 112 Fall 2012 Prof. Michael Kearns.
Interdependent Security Games and Networks Networked Life CSE 112 Spring 2006 Prof. Michael Kearns.
Topology Generation Suat Mercan. 2 Outline Motivation Topology Characterization Levels of Topology Modeling Techniques Types of Topology Generators.
The Structure of Networks with emphasis on information and social networks RU T-214-SINE Summer 2011 Ýmir Vigfússon.
Mining and Searching Massive Graphs (Networks)
1 Sensor Networks and Networked Societies of Artifacts Jose Rolim University of Geneva.
Course Overview and Introduction Networked Life CSE 112 Spring 2005 Prof. Michael Kearns.
Course Introduction and Overview Networked Life CIS 112 Spring 2008 Prof. Michael Kearns.
Strategic Models of Network Formation Networked Life CIS 112 Spring 2010 Prof. Michael Kearns.
Web as Graph – Empirical Studies The Structure and Dynamics of Networks.
Course Introduction and Overview Networked Life CIS 112 Spring 2009 Prof. Michael Kearns.
“The Tipping Point” and the Networked Nature of Society Michael Kearns Computer and Information Science Penn Reading Project 2004.
Game Theory: Whirlwind Review Matrix (normal form) games, mixed strategies, Nash equil. –the basic objects of vanilla game theory –the power of private.
Course Introduction and Overview Networked Life CIS 112 Spring 2010 Prof. Michael Kearns.
Introduction to Game Theory and Behavior Networked Life CIS 112 Spring 2009 Prof. Michael Kearns.
Economic Models of Network Formation Networked Life CIS 112 Spring 2008 Prof. Michael Kearns.
1 Caching Game Dec. 9, 2003 Byung-Gon Chun, Marco Barreno.
Economic Models of Network Formation Networked Life CSE 112 Spring 2006 Prof. Michael Kearns.
Peer-to-Peer and Social Networks Random Graphs. Random graphs E RDÖS -R ENYI MODEL One of several models … Presents a theory of how social webs are formed.
Graph Theory in 50 minutes. This Graph has 6 nodes (also called vertices) and 7 edges (also called links)
School of Management & Information Systems
Prof. Yuan-Shyi Peter Chiu
1 MSCS 237 Distributed Computing Spring 2006 INSTRUCTOR: Dr. Sheikh Iqbal Ahamed Office: Cudahy Hall 386 Phone: Office Hours: Monday 2:00-3:00pm.
Computer Science, Economics, and the Effects of Network Structure
DYNAMICS OF COMPLEX SYSTEMS Self-similar phenomena and Networks Guido Caldarelli CNR-INFM Istituto dei Sistemi Complessi
Contagion in Networks Networked Life NETS 112 Fall 2013 Prof. Michael Kearns.
Network Economics: two examples Marc Lelarge (INRIA-ENS) SIGMETRICS, London June 14, 2012.
Some Analysis of Coloring Experiments and Intro to Competitive Contagion Assignment Prof. Michael Kearns Networked Life NETS 112 Fall 2014.
Structural Properties of Networks: Introduction Networked Life NETS 112 Fall 2015 Prof. Michael Kearns.
Lecture 10: Network models CS 765: Complex Networks Slides are modified from Networks: Theory and Application by Lada Adamic.
Internet Studies. Faculty Members The specialty has now 2 faculty members Prof. Ronen Feldman: Text Mining, Data Mining, Social Media Analysis, Information.
Jure Leskovec Kevin J. Lang Anirban Dasgupta Michael W. Mahoney WWW’ 2008 Statistical Properties of Community Structure in Large Social and Information.
1 Elements of Network Science: CptS / EE Assefaw Gebremedhin Washington State University School of Electrical Engineering and Computer Science.
CompSci The Internet l How valuable is a network? ä Metcalfe’s Law l Domain Name System: translates betweens names and IP addresses l Properties.
Analyzing Networks. Milgram’s Experiments “Six degrees of Separation” Milgram’s letters to various recruits in Nebraska who were asked to forward the.
1 Dr. Michael D. Featherstone Introduction to e-Commerce Network Theory 101.
“Important” Vertices and the PageRank Algorithm Networked Life NETS 112 Fall 2014 Prof. Michael Kearns.
Netlogo demo. Complexity and Networks Melanie Mitchell Portland State University and Santa Fe Institute.
Topics In Social Computing (67810) Module 1 Introduction & The Structure of Social Networks.
Contagion in Networks Networked Life NETS 112 Fall 2015 Prof. Michael Kearns.
Social Networks Some content from Ding-Zhu Du, Lada Adamic, and Eytan Adar.
Lecture 23: Structure of Networks
Structural Properties of Networks: Introduction
The Internet Domain Name System: translates betweens names and IP addresses Properties of the Internet Heterogeneity Redundancy Packet-switched 604 million.
The Power of Networks Six Principles That Connect Our Lives
Structural Properties of Networks: Introduction
Lecture 1: Introduction CS 765: Complex Networks
Course Introduction and Overview
Course Introduction and Overview
Course Introduction and Overview
Course Introduction and Overview
Lecture 23: Structure of Networks
Structural Properties of Networks: Introduction
Networked Life NETS 112 Fall 2018 Prof. Michael Kearns
Peer-to-Peer and Social Networks Fall 2017
Networked Life NETS 112 Fall 2017 Prof. Michael Kearns
Networked Life NETS 112 Fall 2014 Prof. Michael Kearns
Networked Life NETS 112 Fall 2016 Prof. Michael Kearns
The flow could be seen as a network, to develop this network as the underlying mechanism of the marketplace of ideas we can use the idea of.
CS 594: Empirical Methods in HCC Social Network Analysis in HCI
Lecture 23: Structure of Networks
Oliver Schulte Petra Berenbrink Simon Fraser University
Course Introduction and Overview
Networked Life NETS 112 Fall 2019 Prof. Michael Kearns
Presentation transcript:

Course Overview and Introduction Networked Life CSE 112 Spring 2004 Prof. 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 happens over 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 experiments examining 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 quintessential modern 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: – –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