Sociology 204: Social Networks
Princeton University, Spring 2017
- Samuel Clovis
- Romain Ferrali
- Herrissa Lamothe
- Ryan Parsons
- Sarah Reibstein
- Ramina Sotoudeh
- Janet Xu
This course provides students an introduction to the study of social networks. We will focus on understanding the causes and consequences of the patterns of relationships between individuals. Topics will include the small-world puzzle (six degrees of separation), the strength of weak ties, and the spread of diseases and fads.
- Students will be able to describe the major ideas and models used in the study of networks.
- Students will be able to describe the interconnections between the major ideas and models used in the study of networks.
- Students will be able to use the major ideas and models used in the study of networks to gain insight into real-world phenomena.
- Students will be able to evaluate real, modern research that connects the major ideas and models of networks to real-world phenomena.
- Students will be able to begin to create new research that connects the major ideas and models of networks to real-world phenomena.
Assessment and grading
Student grades will be based on the following:
- In-class midterm exam: 25%
The midterm exam will take place on Wednesday March 11, 2015 during the regular class time. If you have a conflict during this time, please read the change of exam time request policy.
- In-class final exam: 45%
The in-class final exam will cover the material from the entire semester. The exam will be Friday, May 19th, 1:30pm - 4:30pm in 50 McCosh Hall
A02 James S McDonnell Hall. This time was set by the registrar. If you need to reschedule the final exam time, please follow the standard university rescheduling policies for final exams.
- Homework/Precept: 30%
There will be weekly assignments that will help you reinforce and extend the ideas from the reading and lectures. The assigns will involve things like replicating the studies that we read about or writing newspaper-style editorial articles.
See the logistics page for more information about time and location, office hours, prerequisites, required text, grading, late assignment policy, regrading procedures, collaboration policy, precept philosophy, precept conflicts,
open access, and Piazza.
The connected age and the small world problem (2/8/17)
- Watts, Preface and Chapter 1. (Available from Blackboard)
- Milgram, S. (1967). The small world problem. Psychology Today, 1:62-67. (Available from Blackboard)
- Travers, J. and Milgram, S. (1969). An experimental study of the small world problem. Sociometry, 32(4):425-443.
- Kleinfeld, J.S. (2002). The small world problem. Society, 39(2):61-66. (Available from Blackboard)
There will be no precept during the first week of the course.
More on the small world problem and some history (2/13/17)
- Granovetter, M. (2003). Ignorance, knowledge, and outcomes in a small world. Science, 301:773-774.
- Dodds, P.S., Muhamad, R., and Watts, D.J. (2003). An experimental study of search in a global social networks. Science, 301:827-829.
- Watts, Chapter 2. (Available from Blackboard)
- Erdos-Reyni random graph animation by Uri Wilensky. (optional)
Understanding the small world phenomena (2/15/17)
Degree distributions and power laws (2/20/17)
- Watts, Chapter 4, 101-114.
- Barabasi, A.L. and Bonabeau, E. (2003) Scale-free networks. Scientific American, 50-59. (Available from Blackboard)
- Barabasi, A.L. and Albert, R. (1999) The emergence of scaling in random networks. Science, 286:509-512.
- Barabasi-Albert random graph animation by Eytan Bakshy and Lada Adamic.
- Liljeros, F. et al. (2001). The web of human sexual contacts. Nature, 411:907-908 with comment and rejoinder.
Social search (2/27/17)
Spread of disease in networks (3/1/17)
The madness of crowds (3/6/17)
Thresholds, cascades, and predictability (3/8/17)
Cascades and fads in cultural markets (3/13/17)
- Hedstrom, P. (2006). Experimental macro sociology: Predicting the next best seller. Science, 311:786-787.
- Salganik, M.J., Dodds, P.S., and Watts, D.J. (2006). Experimental study of inequality and unpredictability in an artificial cultural market. Science, 311:854-856.
- Salganik, M.J., and Watts, D.J. (2008). Leading the herd astray: Experimental study of self-fulfilling prophecies in an artificial cultural market. Social Psychology Quarterly,
Midterm exam (3/15/17)
- 50 minute in-class midterm exam.
Strength of weak ties (3/27/17)
Filter bubbles (3/29/17)
Breaking your bubble (4/3/17)
- Explore Blue Feed, Red Feed, FlipFeed, and/or Escape Your Bubble.
- Eslami, et al. (2015) "I always assumed that I wasn't really that close to [her]:" Reasoning about invisible algorithms in the news feed. Proceedings of the 33rd Annual SIGCHI Conference on Human Factors in Computing Systems, Association for Computing Machinery (ACM): 153-162. (and summary video).
- Constine, J. (2016) How Facebook News Feed Works.
- Roberts, S. (2001) Surprises from self-experimentation: sleep, mood, and weight. Chance 14(2): 7-14.
- Rubin, D.B. (2001) Comment: self-experimentation for causal effects. Chance. 14(2): 16-17.
Measuring tie strength (4/5/17)
Core discussion networks of Americans (4/10/17)
Friends of friends (4/12/17)
Networks and hidden populations at risk for HIV (4/17/17)
Who knows what about who? (4/19/17)
Experimental studies of contagion (4/24/17)
Going viral (4/26/17)
Face-to-face contact networks (5/1/17)
Choose your own adventure (5/3/17)
You have selected the topic for our final meeting: online dating.