Sociology 204: Social Networks, Spring 2017

Sociology 204: Social Networks

Princeton University, Spring 2017

Instructor: Matthew Salganik

Preceptors:

Samuel Clovis

Romain Ferrali

Herrissa Lamothe

Ryan Parsons

Sarah Reibstein

Ramina Sotoudeh

Janet Xu

Class pages on Github, Blackboard, and Piazza

Overview

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.

Learning objectives

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.

Schedule

Week	Monday	Wednesday
1	Introduction (2/6/17)	The connected age and the small world problem (2/8/17)
2	More on the small world problem and some history (2/13/17)	Understanding the small world phenomena (2/15/17)
3	Degree distributions and power laws (2/20/17)	Foci (2/22/17)
4	Social search (2/27/17)	Spread of disease in networks (3/1/17)
5	The madness of crowds (3/6/17)	Thresholds, cascades, and predictability (3/8/17)
6	Cascades and fads in cultural markets (3/13/17)	Midterm exam (3/15/17)
	Spring Break
7	Strength of weak ties (3/27/17)	Filter bubbles (3/29/17)
8	Breaking your bubble (4/3/17)	Measuring tie strength (4/5/17)
9	Core discussion networks of Americans (4/10/17)	Friends of friends (4/12/17)
10	Networks and hidden populations at risk for HIV (4/17/17)	Who knows what about who? (4/19/17)
11	Experimental studies of contagion (4/24/17)	Going viral (4/26/17)
12	Face-to-face contact networks (5/1/17)	Choose your own adventure (5/3/17)

Readings

Introduction (2/6/17)

No reading assigned.

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.

Understanding the small world phenomena (2/15/17)

Watts, Chapter 3.
Watts, D.J. and Strogatz, S.H. (1998). Collective dynamics of 'small-world' networks. Nature 393, 440-442.
Victor, B. (2011). Scientific Communication As Sequential Art.
Watts, D.J. (1999). Networks, dynamics, and the small world phenomenon. American Journal of Sociology, 105(2):493-527.
Watts-Strogatz small world model animation by Eytan Bakshy and Lada Adamic. (optional)

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. (optional)
Liljeros, F. et al. (2001). The web of human sexual contacts. Nature, 411:907-908 with comment and rejoinder.

Foci (2/22/17)

Gladwell, M. (1999). Six degrees of Lois Weisberg. The New Yorker.
Watts, Chapter 4, 114-129.
Feld, S.L. (1981) The focused organization of social ties. American Journal of Sociology, 86(5):1015-1035.

Social search (2/27/17)

Watts, Chapter 5.
Lee, N.H. (1969). The Search for an Abortionist: Preface, Chapter 1, and Chapter 5. (Available from Blackboard).

Spread of disease in networks (3/1/17)

Watts, Chapter 6.
Bearman, P.S., Moody, J.M., and Stovel, K. (2004). Chains of affection: The structure of adolescent romantic and sexual networks. American Journal of Sociology, 110(1):44-91.

The madness of crowds (3/6/17)

Watts, Chapter 7.
Asch, S.E. (1955). Opinions and social pressure. Scientific American, 193(5):31-35. (Available on Blackboard)
Easley D. and Kleinberg, J. (2010). Networks, Crowds, and Markets: Chapter 16. (skim mathematical model in Sections 16.3-16.6)
Tierney, J. (2007). Diet and fat: A severe case of mistaken consensus. New York Times.

Thresholds, cascades, and predictability (3/8/17)

Gladwell, M. (1996). The tipping point. The New Yorker. (Available on Blackboard)
Watts, Chapter 8.
Watts, D.J. (2002). A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences 99:5766-5771.

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, 71:338-355.

Midterm exam (3/15/17)

50 minute in-class midterm exam.

Strength of weak ties (3/27/17)

Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380.
Smith, S. (2005). "Don't put my name on it": Social capital activation and job-finding assistance among the black urban poor. American Journal of Sociology, 111(1), 1-57.

Filter bubbles (3/29/17)

Pariser, E. (2011). Beware online 'filter bubbles'. TED talk.
Weisberg, J. (2011). Bubble Trouble: Is Web personalization turning us into solipsistic twits. Slate.
Bakshy, E., Messing, S., and Adamic, L.A. (2015) Exposure to ideologically diverse news and opinion on Facebook. Science.
Sandvig, C. (2015) The Facebook 'it’s not our fault' study. Social Media Collective Research Blog.

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)

Marsden, P.V. and Campbell, K.E. (1984) Measuring tie strength. Social Forces 63(2):482-501.
Gilbert, E. and Karahalios, K. (2009). Predicting tie strength with social media Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 211-220.
Jones, J.J., et al. (2013). Inferring tie strength from online directed behavior. PLOS One, 8(1):e521168. (Note: When reading this paper, please read the Materials and Methods section after the Introduction and before Results.)

Core discussion networks of Americans (4/10/17)

Fountain, H. (2006). The lonely American just got a bit lonelier. The New York Times, July 2.
McPherson, M., Smith-Lovin, L., and Brashears, M.E. (2006). Social isolation in America: Changes in core discussion networks over two decades. American Sociological Review, 71(3):353-375.

Friends of friends (4/12/17)

Strogatz, S. (2012). Friends you can count on. New York Times, September 17.
Christakis, N.A. (2010). How social networks predict epidemics. TED Talk.
Christakis, N.A. and Fowler, J.H. (2010). Social network sensors for early detection of contagious outbreaks. PLoS ONE 5(9):e12948.

Networks and hidden populations at risk for HIV (4/17/17)

Bernard, H.R. et al. (2010). Counting hard-to-count populations: The network scale-up method for public health. Sexually Transmitted Infections, 86:ii11-ii15.
Feehan et al. (2016). Quality vs. Quantity: A survey experiment to improve the network scale-up method. American Journal of Epidemiology 183(8): 747-757.

Who knows what about who? (4/19/17)

Goel, S. et al. (2010) Real and perceived attitude agreement in social networks. Journal of Personality and Social Psychology.
Cowan, S. (2014) Secrets and Misperceptions: The Creation of Self-Fulfilling Illusions Sociological Science.

Experimental studies of contagion (4/24/17)

Nickerson, D.W. (2008). Is voting contagious? Evidence from two field experiments. American Political Science Review, 102(1):49-57.
LaCour, M.J. and Green, D.P. (2014). When contact changes minds: An experiment on transmission of support for gay equality. Science, 346(6215):1366-1369.

Kramer, A.D.I. et al. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences.

Going viral (4/26/17)

Goel, S. et al (2015). The structural virality of online diffusion. Management Science.
Facebook Data Science (2014) Can cascades be predicted?
Cheng et al. (2014) Can cascades be predicted? WWW.

Face-to-face contact networks (5/1/17)

Mossong, J. et al. (2008). Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases. PLoS Medicine 5(3):e74.
Salathé, M. et al. (2010). A High-Resolution Human Contact Network for Infectious Disease Transmission. Proceedings of the National Academy of Sciences 107(51):22020–22025.

Choose your own adventure (5/3/17)

You have selected the topic for our final meeting: online dating.

Ansari, A. and Klinenberg, E. (2015). How to Make Online Dating Work New York Times.
Kercher, S. (2017). First Comes Tinder. Then Comes Marriage? New York Times.
Tinder's: Modern dating myths.
Andreson et al. (2014) Political Ideology and Racial Preferences in Online Dating Sociological Science with comment and rejoinder.

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