Spring 2017

Demography 260: Social Networks

Dennis M. Feehan

feehan@berkeley.edu

Class meetings: Wednesdays, 2-5pm Demography Seminar Room
Office hours: by appointment (please send me an email and we can find a time)

Overview

This course provides a broad introduction to the empirical and theoretical study of social networks. We will cover classic and contemporary studies, beginning with fundamental definitions and models, and then moving through a range of topics, including models of network formation and structure (homophily, foci, communities); dynamic processes on networks (contagion, influence, and disease models); collaborative networks; personal networks; online networks; and network sampling and data collection. The course material is intended to be of interest to students from a wide range of disciplinary backgrounds, including demography, sociology, statistics, computer science, and related fields.

I’m currently revising the syllabus from last year. Please re-check the syllabus before you start each week’s reading; it will be updated as the semester progresses

Requirements

The requirements of the class are designed to achieve two goals: the first goal is to become familiar with some classic and contemporary research about social networks through reading papers and discussing them; and, second, to write a research paper. You should think of the research paper as the first draft of a project that you might be able to continue working on beyond this class.

NB: Please read each week’s articles in the order they are listed on the syllabus

Week 1 (1/18): Fundamentals and background

Readings to discuss:

We won’t explicitly discuss chapter 7 of the Newman book in class, but it’s also worth reading at some point; it describes several different network measures that are often mentioned in the literature.

OPTIONAL: This paper gives a good overview of the study of social networks. We won’t explicitly discuss it in class, but it would be helpful to read at some point during the semester.

Related, but we won’t have time to discuss in class:

Week 2 (1/25): sampling, data collection, statistics

Readings to discuss:

I’ll talk a little bit about random graph models; if you want extra background, the Newman chapter is a good reference:

Background and related:

Week 3 (2/1): Kinship networks

Readings to discuss:

TBA

Week 4 (2/8): Network models, connectivity, and small worlds

Readings to discuss:

Background and related:

Week 5 (2/15): Communities, social capital, SOWT

Readings we will discuss:

Also interesting (but we won’t have time to discuss in class):

Demography-specific:

Week 6 (2/22): Communities, social capital cont.

Also interesting (but we won’t have time to discuss in class):

Week 7 (3/1): Network formation, homophily

Also interesting, but we will not have time to discuss:

Week 8 (3/8): Network formation, time

Also interesting (but we won’t have time to discuss in class):

3/15 : NO CLASS

Week 9 (3/22): Network formation, collaboration and cooperation

Also interesting, but we will not have time to discuss:

3/29: Spring break

Week 10 (4/5): Contagion and influence - simple contagion and epidemics; methodological challenges

Also interesting, but we will not have time to discuss:

Week 11 (4/12): Contagion and influence - complex contagion

Also interesting, but we will not have time to discuss

Especially relevant for demography:

Week 12 (4/19): Contagion and influence - peer effects

Also interesting, but we won’t have time to discuss:

4/26: PAA

Mini-conference: TBA

Optional wrap-up: