Demography 260:
Social Networks

Class meetings: Mondays, 10am-1pm 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, likely including models of network formation and structure (homophily, foci, communities); dynamic processes on networks (contagion, influence, and disease models); collaborative 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.

Please re-check the syllabus before you start each week’s reading; it will be updated as the semester progresses

Requirements

In addition to reading the material and participating in class discussions, there are three requirements for the class:

• reading and class participation

• response memos

  For 6 of the 8 weeks, please write a short response memo (1 to 2 pages). You can pick which weeks you write the memos. The goal of these memos is to help you focus your thoughts about the reading prior to our group discussion; to help me get an understanding of what parts of the reading our discussion should focus on; and to serve as a reference for you in the future. The format of the memos is open, but at a minimum I would like you to be sure to (1) quickly summarize how the readings relate to one another (if you think they do); and (2) briefly describe at least one research idea that the readings generated for you (this could be a single sentence, or the entire memo; it’s up to you). The response memos are due by noon on the Sunday before each class.

• project proposal

  In lieu of a final paper, you will write a short proposal for a research project (about 5 pages). Your proposal should identify an important problem to be studied, briefly review the related literature, and then describe your proposed research design. Be sure to describe the data you will use (it may exist already, or it may be data you could collect or scrape from the web), your hypotheses, and the methods you plan to use. The purpose of this proposal is to connect the topics of this class to your actual research, so my hope is that this will be an opportunity to get some feedback on an idea you care about, and that you might continue to pursue beyond class. These proposals are due by Wednesday, May 4 at 5pm.

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

Week 1 (2/29): Fundamentals and background

Readings to discuss:

• Stephen P. Borgatti et al., “Network Analysis in the Social Sciences,” Science 323, no. 5916 (2009): 892–895, http://science.sciencemag.org/content/323/5916/892.short.
• Carter T. Butts, “Revisiting the Foundations of Network Analysis,” Science 325, no. 5939 (2009): 414, http://science.sciencemag.org/content/325/5939/414.
• Mustafa Emirbayer, “Manifesto for a Relational Sociology,” American Journal of Sociology 103, no. 2 (1997): 281–317, http://www.jstor.org/stable/10.1086/231209.
• Hans-Peter Kohler et al., “The Social and the Sexual: Networks in Contemporary Demographic Research” (2013), http://repository.upenn.edu/psc_working_papers/41/.
• Christine A. Bachrach, “Culture and Demography: From Reluctant Bedfellows to Committed Partners,” Demography 51, no. 1 (2014): 3–25, http://link.springer.com/article/10.1007/s13524-013-0257-6.
• Scott L. Feld, “Why Your Friends Have More Friends Than You Do,” American Journal of Sociology (1991): 1464–1477, http://www.jstor.org/stable/2781907.
• R. I. M. Dunbar and Susanne Shultz, “Evolution in the Social Brain,” Science 317, no. 5843 (September 2007): 1344–1347, http://science.sciencemag.org/content/317/5843/1344.
• David Lazer et al., “Computational Social Science,” Science 323, no. 5915 (February 2009): 721–723, http://science.sciencemag.org/content/323/5915/721.
• Nathan Eagle and Alex Sandy Pentland, “Eigenbehaviors: Identifying Structure in Routine,” Behavioral Ecology and Sociobiology 63, no. 7 (2009): 1057–1066, http://link.springer.com/article/10.1007/s00265-009-0739-0.
• Mark Newman, Networks: An Introduction (Oxford University Press, 2010), ch. 6. - some mathematical background

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.

Week 2 (3/7): sampling, data collection, statistics

Readings to discuss:

• Miller McPherson, Lynn Smith-Lovin, and Matthew E. Brashears, “Social Isolation in America: Changes in Core Discussion Networks over Two Decades,” American Sociological Review 71, no. 3 (2006): 353–375, http://asr.sagepub.com/content/71/3/353.short.
  • Claude S. Fischer, “The 2004 GSS Finding of Shrunken Social Networks: An Artifact?” American Sociological Review 74, no. 4 (2009): 657–669, http://asr.sagepub.com/content/74/4/657.short.
  • Miller McPherson, Lynn Smith-Lovin, and Matthew E. Brashears, “Models and Marginals: Using Survey Evidence to Study Social Networks,” American Sociological Review 74, no. 4 (2009): 670–681, http://asr.sagepub.com/content/74/4/670.short.
  • Anthony Paik and Kenneth Sanchagrin, “Social Isolation in America An Artifact,” American Sociological Review (2013): 0003122413482919, http://asr.sagepub.com/content/early/2013/04/05/0003122413482919.abstract.
• Nathan Eagle, Alex Sandy Pentland, and David Lazer, “Inferring Friendship Network Structure by Using Mobile Phone Data,” Proceedings of the National Academy of Sciences 106, no. 36 (2009): 15274–15278, https://www.pnas.org/content/106/36/15274.full.
• Sharad Goel, Winter Mason, and Duncan J. Watts, “Real and Perceived Attitude Agreement in Social Networks.” Journal of Personality and Social Psychology 99, no. 4 (2010): 611, http://psycnet.apa.org/journals/psp/99/4/611/.
• Sharad Goel and Matthew J. Salganik, “Assessing Respondent-Driven Sampling,” Proceedings of the National Academy of Sciences 107, no. 15 (2010): 6743–6747, http://www.pnas.org/content/107/15/6743.short.
• Rwanda mortality paper (appendix is optional; I will email this out to the class)
• Newman, Networks, ch. 12. - Poisson random graph models

Background and related:

• Peter V. Marsden, “Network Data and Measurement,” Annual Review of Sociology (1990): 435–463, http://www.jstor.org/stable/2083277.
• Peter D. Hoff, Adrian E. Raftery, and Mark S. Handcock, “Latent Space Approaches to Social Network Analysis,” Journal of the American Statistical Association 97, no. 460 (2002): 1090–1098, http://www.tandfonline.com/doi/abs/10.1198/016214502388618906.
• Cathleen McGrath, Jim Blythe, and David Krackhardt, “The Effect of Spatial Arrangement on Judgments and Errors in Interpreting Graphs,” Social Networks 19, no. 3 (1997): 223–242, http://www.sciencedirect.com/science/article/pii/S0378873396002997.
• Martin Krzywinski et al., “Hive Plots—rational Approach to Visualizing Networks,” Briefings in Bioinformatics (2011): bbr069, https://bib.oxfordjournals.org/content/early/2011/12/09/bib.bbr069.full.

Week 3 (3/14): Connectivity and small worlds

Readings to discuss:

• Stanley Milgram, “The Small World Problem,” Psychology Today 2, no. 1 (1967): 60–67, http://measure.igpp.ucla.edu/GK12-SEE-LA/Lesson_Files_09/Tina_Wey/TW_social_networks_Milgram_1967_small_world_problem.pdf.
• Jeffrey Travers and Stanley Milgram, “An Experimental Study of the Small World Problem,” Sociometry (1969): 425–443, http://www.jstor.org/stable/2786545.
• Duncan J. Watts and Steven H. Strogatz, “Collective Dynamics of ‘Small-World’ Networks,” Nature 393, no. 6684 (1998): 440–442, http://www.nature.com/nature/journal/v393/n6684/abs/393440a0.html.
• Jon M. Kleinberg, “Navigation in a Small World,” Nature 406, no. 6798 (2000): 845–845, http://www.nature.com/nature/journal/v406/n6798/abs/406845a0.html.
• Duncan J. Watts, Peter Sheridan Dodds, and Mark EJ Newman, “Identity and Search in Social Networks,” Science 296, no. 5571 (2002): 1302–1305, http://science.sciencemag.org/content/296/5571/1302.short.
• Mark Granovetter, “Ignorance, Knowledge, and Outcomes in a Small World,” Science 301, no. 5634 (2003): 773–774, http://science.sciencemag.org/content/301/5634/773.short.
• Peter Sheridan Dodds, Roby Muhamad, and Duncan J. Watts, “An Experimental Study of Search in Global Social Networks,” Science 301, no. 5634 (2003): 827–829, http://science.sciencemag.org/content/301/5634/827.short.
• Brian Uzzi and Jarrett Spiro, “Collaboration and Creativity: The Small World Problem,” American Journal of Sociology 111, no. 2 (2005): 447–504, http://www.jstor.org/stable/10.1086/432782.

Background and related:

• Duncan J. Watts, Six Degrees: The Science of a Connected Age (WW Norton & Company, 2004), ch. 1-3.
• Seth A. Marvel et al., “The Small-World Effect Is a Modern Phenomenon,” ArXiv Preprint ArXiv:1310.2636 (2013), http://arxiv.org/abs/1310.2636.
• a relevant Facebook research note
• and a relevant comment by Duncan Watts

Week 4 (3/28): Social capital and communities

Readings we will discuss:

• Mark S. Granovetter, “The Strength of Weak Ties,” American Journal of Sociology (1973): 1360–1380, http://www.jstor.org/stable/2776392.
• Scott L. Feld, “The Focused Organization of Social Ties,” American Journal of Sociology (1981): 1015–1035, http://www.jstor.org/stable/2778746.
• Thomas A. DiPrete et al., “Segregation in Social Networks Based on Acquaintanceship and Trust,” American Journal of Sociology 116, no. 4 (2011): 1234–83, http://www.jstor.org/stable/10.1086/659100.
• Elizabeth Fussell and Douglas S. Massey, “The Limits to Cumulative Causation: International Migration from Mexican Urban Areas,” Demography 41, no. 1 (2004): 151–171, http://link.springer.com/article/10.1353/dem.2004.0003.
• Mark EJ Newman and Michelle Girvan, “Finding and Evaluating Community Structure in Networks,” Physical Review E 69, no. 2 (2004): 026113, http://journals.aps.org/pre/abstract/10.1103/PhysRevE.69.026113.
• Amir Goldberg, “Mapping Shared Understandings Using Relational Class Analysis: The Case of the Cultural Omnivore Reexamined,” American Journal of Sociology 116, no. 5 (2011): 1397–1436, http://www.jstor.org/stable/10.1086/657976.
• Nathan Eagle, Michael Macy, and Rob Claxton, “Network Diversity and Economic Development,” Science 328, no. 5981 (2010): 1029–1031, http://science.sciencemag.org/content/328/5981/1029.short.

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

• Ronald L. Breiger, “The Duality of Persons and Groups,” Social Forces 53, no. 2 (1974): 181–190, http://sf.oxfordjournals.org/content/53/2/181.short.
• Harrison C. White, Scott A. Boorman, and Ronald L. Breiger, “Social Structure from Multiple Networks. I. Blockmodels of Roles and Positions,” American Journal of Sociology (1976): 730–780, http://www.jstor.org/stable/2777596.
• James S. Coleman, “Social Capital in the Creation of Human Capital,” American Journal of Sociology (1988): S95–S120, http://www.jstor.org/stable/2780243.
• the theory/background section of this paper is an excellent review of homophily: Andreas Wimmer and Kevin Lewis, “Beyond and Below Racial Homophily: ERG Models of a Friendship Network Documented on Facebook,” American Journal of Sociology 116, no. 2 (2010): 583–642, http://www.jstor.org/stable/10.1086/653658.
• Alejandro Portes, “Social Capital: Its Origins and Applications in Modern Sociology,” Lesser, Eric L. Knowledge and Social Capital. Boston: Butterworth-Heinemann (2000): 43–67.
• Douglas S. Massey, “Social Structure, Household Strategies, and the Cumulative Causation of Migration,” Population Index (1990): 3–26, http://www.jstor.org/stable/3644186.
• J.-P. Onnela et al., “Structure and Tie Strengths in Mobile Communication Networks,” Proceedings of the National Academy of Sciences 104, no. 18 (2007): 7332–7336, http://www.pnas.org/content/104/18/7332.short.
• Mark Granovetter, The Strength of Weak Ties: A Network Theory Revisited (JSTOR, 1981), http://www.jstor.org/stable/pdf/202051.pdf.
• Brian Karrer and Mark EJ Newman, “Stochastic Blockmodels and Community Structure in Networks,” Physical Review E 83, no. 1 (2011): 016107, http://journals.aps.org/pre/abstract/10.1103/PhysRevE.83.016107.
• Ronald S. Burt, “Structural Holes and Good Ideas,” American Journal of Sociology 110, no. 2 (2004): 349–399, http://www.jstor.org/stable/10.1086/421787.
• Mark Granovetter, “Economic Action and Social Structure: The Problem of Embeddedness,” American Journal of Sociology (1985): 481–510, http://www.jstor.org/stable/2780199.
• Alejandro Portes and Julia Sensenbrenner, “Embeddedness and Immigration: Notes on the Social Determinants of Economic Action,” American Journal of Sociology (1993): 1320–1350, http://www.jstor.org/stable/2781823.

Week 5 (4/4): Network formation, time

• Albert-László Barabási and Réka Albert, “Emergence of Scaling in Random Networks,” Science 286, no. 5439 (1999): 509–512, http://science.sciencemag.org/content/286/5439/509.short.
• Fredrik Liljeros et al., “The Web of Human Sexual Contacts,” Nature 411, no. 6840 (2001): 907–908, http://www.nature.com/nature/journal/v411/n6840/full/411907a0.html.
  • James Holland Jones and Mark S. Handcock, “Social Networks (Communication Arising): Sexual Contacts and Epidemic Thresholds,” Nature 423, no. 6940 (2003): 605–606, http://www.nature.com/nature/journal/v423/n6940/full/423605a.html.
  • Fredrik Liljeros et al., “Social Networks (Communication Arising): Sexual Contacts and Epidemic Thresholds,” Nature 423, no. 6940 (2003): 606–606, http://www.nature.com/nature/journal/v423/n6940/full/423606a.html.
• Peter S. Bearman, James Moody, and Katherine Stovel, “Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks1,” American Journal of Sociology 110, no. 1 (2004): 44–91, http://www.jstor.org/stable/10.1086/386272.
• Gueorgi Kossinets and Duncan J. Watts, “Empirical Analysis of an Evolving Social Network,” Science 311, no. 5757 (2006): 88–90, http://science.sciencemag.org/content/311/5757/88.short.
• Gueorgi Kossinets and Duncan J. Watts, “Origins of Homophily in an Evolving Social Network,” American Journal of Sociology 115, no. 2 (2009): 405–450, http://www.jstor.org/stable/10.1086/599247.
• Coren L. Apicella et al., “Social Networks and Cooperation in Hunter-Gatherers,” Nature 481, no. 7382 (2012): 497–501, http://www.nature.com/nature/journal/v481/n7382/full/nature10736.html.
• Tuan Q. Phan and Edoardo M. Airoldi, “A Natural Experiment of Social Network Formation and Dynamics,” Proceedings of the National Academy of Sciences 112, no. 21 (2015): 6595–6600, http://www.pnas.org/content/112/21/6595.short.

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

• Mark EJ Newman, “Coauthorship Networks and Patterns of Scientific Collaboration,” Proceedings of the National Academy of Sciences 101, no. suppl 1 (2004): 5200–5205, http://www.pnas.org/content/101/suppl_1/5200.short.
• Roger Guimera et al., “Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance,” Science 308, no. 5722 (2005): 697–702, http://science.sciencemag.org/content/308/5722/697.short.

Week 6 (4/11): Time and collaboration, cont.; intro to contagion and influence

• Winter Mason and Duncan J. Watts, “Collaborative Learning in Networks,” Proceedings of the National Academy of Sciences 109, no. 3 (2012): 764–769, http://www.pnas.org/content/109/3/764.short.
• Jing Wang, Siddharth Suri, and Duncan J. Watts, “Cooperation and Assortativity with Dynamic Partner Updating,” Proceedings of the National Academy of Sciences 109, no. 36 (2012): 14363–14368, http://www.pnas.org/content/109/36/14363.short.
• Mark Granovetter, “Threshold Models of Collective Behavior,” American Journal of Sociology (1978): 1420–1443, http://www.jstor.org/stable/2778111.
• Duncan J. Watts and Peter Sheridan Dodds, “Influentials, Networks, and Public Opinion Formation,” Journal of Consumer Research 34, no. 4 (2007): 441–458, http://jcr.oxfordjournals.org/content/34/4/441.abstract.
• Paul DiMaggio and Filiz Garip, “How Network Externalities Can Exacerbate Intergroup Inequality,” American Journal of Sociology 116, no. 6 (2011): 1887–1933, http://www.jstor.org/stable/10.1086/659653.
• Nicholas A. Christakis and James H. Fowler, “Social Network Sensors for Early Detection of Contagious Outbreaks,” PloS One 5, no. 9 (2010): e12948, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0012948.

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

• Duncan J. Watts, “A Simple Model of Global Cascades on Random Networks,” Proceedings of the National Academy of Sciences 99, no. 9 (2002): 5766–5771, http://www.pnas.org/content/99/9/5766.short.
• Winter Mason, Siddharth Suri, and Duncan J. Watts, “Long-Run Learning in Games of Cooperation,” in Proceedings of the Fifteenth ACM Conference on Economics and Computation (ACM, 2014), 821–838, http://dl.acm.org/citation.cfm?id=2602892.
• Pejman Rohani, Xue Zhong, and Aaron A. King, “Contact Network Structure Explains the Changing Epidemiology of Pertussis,” Science 330, no. 6006 (2010): 982–985, http://science.sciencemag.org/content/330/6006/982.short.
• Mirjam Kretzschmar, Richard G. White, and Michel Caraël, “Concurrency Is More Complex Than It Seems,” AIDS (London, England) 24, no. 2 (2010): 313, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2887386/.
• Martina Morris and Mirjam Kretzschmar, “Concurrent Partnerships and the Spread of HIV,” Aids 11, no. 5 (1997): 641–648, http://journals.lww.com/aidsonline/Abstract/1997/05000/Concurrent_partnerships_and_the_spread_of_HIV.12.aspx.
• Damon Centola, “The Social Origins of Networks and Diffusion,” American Journal of Sociology 120, no. 5 (2015): 1295–1338, http://www.jstor.org/stable/10.1086/681275.
• Damon Centola and Michael Macy, “Complex Contagions and the Weakness of Long Ties,” American Journal of Sociology 113, no. 3 (2007): 702–734, http://www.jstor.org/stable/10.1086/521848.

Week 7 (4/18): Contagion and influence

• Nicholas A. Christakis and James H. Fowler, “The Spread of Obesity in a Large Social Network over 32 Years,” New England Journal of Medicine 357, no. 4 (2007): 370–379, http://www.nejm.org/doi/full/10.1056/nejmsa066082.
• Russell Lyons, “The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis,” Statistics, Politics, and Policy 2, no. 1 (2011), http://www.degruyter.com/view/j/spp.2011.2.issue-1/spp.2011.2.1.1024/spp.2011.2.1.1024.xml.
• Controversy over the C-F findings on the contagion of obesity (blog post by Andrew Gelman)
• Johan Ugander et al., “Structural Diversity in Social Contagion,” Proceedings of the National Academy of Sciences 109, no. 16 (2012): 5962–5966, http://www.pnas.org/content/109/16/5962.short.
• Nicoletta Balbo and Nicola Barban, “Does Fertility Behavior Spread Among Friends?” American Sociological Review 79, no. 3 (2014): 412–431, http://asr.sagepub.com/content/79/3/412.short.

Also interesting, but we will not have time to discuss

• Social Contagion Theory: Examining Dynamic Social Networks and Human Behavior (a response to some criticisms of Christakis and Fowler)
• Cosma Rohilla Shalizi and Andrew C. Thomas, “Homophily and Contagion Are Generically Confounded in Observational Social Network Studies,” Sociological Methods & Research 40, no. 2 (2011): 211–239, http://smr.sagepub.com/content/40/2/211.short.
• Charles F. Manski, “Identification of Endogenous Social Effects: The Reflection Problem,” The Review of Economic Studies 60, no. 3 (1993): 531–542, http://restud.oxfordjournals.org/content/60/3/531.short.

Week 8 (4/25): Contagion and influence

• Hans-Peter Kohler, Jere R. Behrman, and Susan C. Watkins, “Social Networks and HIV/AIDS Risk Perceptions,” Demography 44, no. 1 (2007): 1–33, http://link.springer.com/article/10.1353/dem.2007.0006.
• David W. Nickerson, “Is Voting Contagious? Evidence from Two Field Experiments,” American Political Science Review 102, no. 01 (2008): 49–57, http://journals.cambridge.org/abstract_S0003055408080039.
• Damon Centola, “The Spread of Behavior in an Online Social Network Experiment,” Science 329, no. 5996 (2010): 1194–1197, http://science.sciencemag.org/content/329/5996/1194.short.
• Eytan Bakshy et al., “Social Influence in Social Advertising: Evidence from Field Experiments,” in Proceedings of the 13th ACM Conference on Electronic Commerce (ACM, 2012), 146–161, http://dl.acm.org/citation.cfm?id=2229027.
• Abhijit Banerjee et al., “The Diffusion of Microfinance,” Science 341, no. 6144 (2013): 1236498, http://science.sciencemag.org/content/341/6144/1236498.short.

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

• Robert M. Bond et al., “A 61-Million-Person Experiment in Social Influence and Political Mobilization,” Nature 489, no. 7415 (2012): 295–298, http://www.nature.com/nature/journal/v489/n7415/abs/nature11421.html.
• Eytan Bakshy et al., “The Role of Social Networks in Information Diffusion,” ArXiv:1201.4145 [Physics] (January 2012), http://arxiv.org/abs/1201.4145.
• Eytan Bakshy, Dean Eckles, and Michael S. Bernstein, “Designing and Deploying Online Field Experiments,” in Proceedings of the 23rd International Conference on World Wide Web (ACM, 2014), 283–292, http://dl.acm.org/citation.cfm?id=2567967.
• Dean Eckles, Brian Karrer, and Johan Ugander, “Design and Analysis of Experiments in Networks: Reducing Bias from Interference,” ArXiv Preprint ArXiv:1404.7530 (2014), http://arxiv.org/abs/1404.7530.

Optional wrap-up:

• Duncan J. Watts, “The‘ New’ Science of Networks,” Annual Review of Sociology (2004): 243–270, http://www.jstor.org/stable/29737693.
• Mark EJ Newman and Juyong Park, “Why Social Networks Are Different from Other Types of Networks,” Physical Review E 68, no. 3 (2003): 036122, http://journals.aps.org/pre/abstract/10.1103/PhysRevE.68.036122.