The next figure depicts friendships among high-school students in one of

the high-schools in what's known as the Add Health data set.

Nodes are coded by race, and

you can see this network exhibits what's known homophily.

Students are strongly segregated by race.

How can we measure and explain the formation of this network?

What's the impact on learning and

communication of the segregation in such a network?

So there's lots of interesting questions there.

This third figure is another fascinating one.

It depicts the marriages among 16 major families in 15th century Florence.

This was a period during which the Medici rose to prominence and

some of the key marriages here were engineered by Cosimo de' Medici.

So how do we measure the positions of different families?

Can this network help us explain why the Medici rose to power during this period?

So the course will bring together models not only from economics and sociology but

also from computer science, physics, random graph theory and mathematics,

statistics.

And my aim is to provide a synthesis and an introduction to the very multi-

interdisciplinary approaches of analyzing networks.

It should give you a toolbox to go forward with and

draw upon as you analyze model networks.

And we'll study basic measures of networks,

models of network formation, models of diffusion, learning, contagion.

As well as how networks impact behaviors.

And we'll be using some statistical techniques for analyzing networks.

And I'll point out some important areas for new research as we go along.

What sort of background do you need?

Well, the course is going to assume that you're comfortable with matrix algebra,

since coding and analyzing networks these days makes heavy use of matrices.

We'll also be using basic concepts from probability and

statistics and some light calculus.

There'll be a little bit of game theories in the course but

I'll make sure that will be self-contained.

And you should feel pretty comfortable on a computer.

We'll be exploring some network data as we go along.