Social Networks
DEMOG C280/SOCIOL C273N
Class meetings: Wednesdays, 2-5pm Demography Seminar Room
Office hours: by appointment (please send me an email and we can find a time)
Email: [email protected]
Web: www.dennisfeehan.org/teaching
Piazza page
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.
Please re-check the syllabus before you start each week's reading; it will be updated as the semester progresses
Requirements and assignments
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 the second goal is 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.
reading and class participation
Each week, you should read the assigned materials and show up to class prepared to discuss them. There are two additional requirements: (1) One of the weeks you will also be in charge of organizing the discussion (possibly with a partner). (2) For two of the weeks when you are not leading the discussion, you will be asked to pick one additional paper to briefly present to the class. (This could be a paper on the syllabus that we don't all have time to discuss, or it could be a different paper in the same topic area that is of interest to you.) Once you have decided which paper you will present, please announce it on Piazza, so that nobody else picks the same paper.
response memos
For 6 of the class meetings, please write a short response memo (1 to 2 pages). You can pick which weeks you write the memos. These memos should not take an enormous amount of time to write. The main goal of these memos is to help you focus your thoughts about the reading prior to our group discussion; to help us 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 Tuesday before each class; please post your memo as a Piazza post, so we can all see it before class..
final paper
You will write a short (10-20 pages) research paper to conclude the class. Leading up to the end of the class, you will submit a brief proposal (1 paragraph to 1 page) and lit review (1 or more pages) that set up the paper you plan to work on. The purpose of the proposal and lit review is to give you some feedback on the initial idea / data source / etc before you invest a lot of time writing an actual paper. Your final paper should identify an important problem to be studied, briefly review the related literature, describe your proposed research design, and present some (possibly preliminary) empirical findings.
The purpose of this paper 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.
The paper is due in class on Friday, May 10.
NB: Please read each week's articles in the order they are listed on the syllabus
Grading scheme
The assignments are described in the Requirements section, above. The final grade will be a weighted average of the scores on those assignments where the weights are:
- Response memos (20%)
- Reading and participation (30%)
- Final paper (50%)
Week 1 (1/23): Fundamentals and background
Read for background:
- 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.
- Mark Newman, Networks: An Introduction (Oxford University Press, 2010), ch. 6. (sections 6.1-6.7;6.9-6.11; optionally 6.12-6.13) - some mathematical background.
Readings to discuss:
- 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.
- 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.
- Alistair Sutcliffe et al., “Relationships and the Social Brain: Integrating Psychological and Evolutionary Perspectives,” British Journal of Psychology 103, no. 2 (2012): 149–168, http://onlinelibrary.wiley.com/doi/10.1111/j.2044-8295.2011.02061.x/full.
- 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.
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: The papers at the end of the syllabus give a good overview of the study of social networks. We won't explicitly discuss them in class, but they would be helpful to read at some point during the semester.
Related, but we won't have time to discuss in class:
- 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.
- 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.
- David Lazer et al., “Computational Social Science,” Science 323, no. 5915 (February 2009): 721–723.
- R. I. M. Dunbar and Susanne Shultz, “Evolution in the Social Brain,” Science 317, no. 5843 (September 2007): 1344–1347.
Week 2 (1/30): Sampling, data collection, statistics
Readings to discuss:
- Related to McPherson et al (2006) [from last week]
- 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.
- [SKIM] 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.
- [READ ABSTRACT] 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.
- 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/.
- 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.
- [READ ABSTRACT] 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.
- [SKIM] 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.
Background and related (we won't discuss):
- Peter V. Marsden, “Network Data and Measurement,” Annual Review of Sociology (1990): 435–463, http://www.jstor.org/stable/2083277.
- Peter V. Marsden, “Recent Developments in Network Measurement,” Models and Methods in Social Network Analysis 8 (2005): 30.
- Matthew E. Brashears, “’Trivial’ Topics and Rich Ties: The Relationship Between Discussion Topic, Alter Role, and Resource Availability Using the ‘Important Matters’ Name Generator,” Sociological Science 1 (November 2014): 493–511.
- Peter Bearman and Paolo Parigi, “Cloning Headless Frogs and Other Important Matters: Conversation Topics and Network Structure,” Social Forces 83, no. 2 (December 2004): 535–557.
- Byungkyu Lee and Peter Bearman, “Important Matters in Political Context,” Sociological Science 4 (2017): 1–30, https://www.sociologicalscience.com/articles-v4-1-1/.
- Casey A. Klofstad, Anand Edward Sokhey, and Scott D. McClurg, “Disagreeing About Disagreement: How Conflict in Social Networks Affects Political Behavior,” American Journal of Political Science 57, no. 1 (2013): 120–134.
- Diana C. Mutz, “Cross-Cutting Social Networks: Testing Democratic Theory in Practice,” American Political Science Review 96, no. 1 (2002): 111–126.
Week 3 (2/6): Sampling, data collection, statistics
Readings to discuss:
- Sarah K. Cowan and Delia Baldassarri, “‘It Could Turn Ugly’: Selective Disclosure of Attitudes in Political Discussion Networks,” Social Networks (2017), https://www.sciencedirect.com/science/article/pii/S037887331630404X.
- 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.
- 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)
- Tian Zheng, Matthew J. Salganik, and Andrew Gelman, “How Many People Do You Know in Prison?: Using Overdispersion in Count Data to Estimate Social Structure in Networks,” Journal of the American Statistical Association 101, no. 474 (June 2006): 409–423.
I'll talk a little bit about random graph models; if you want extra background, the Newman chapter is a good reference:
- Newman, Networks, ch. 12. - Poisson random graph models
Related (we won't have time to discuss):
- Michael Bailey et al., “Social Connectedness: Measurement, Determinants, and Effects,” Journal of Economic Perspectives 32, no. 3 (2018): 259–80.
Week 4 (2/13): Network models, 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.
- 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.
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
- David Liben-Nowell et al., “Geographic Routing in Social Networks,” Proceedings of the National Academy of Sciences of the United States of America 102, no. 33 (2005): 11623–11628, http://www.pnas.org/content/102/33/11623.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.
- 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.
Week 5 (2/20): Communities, social capital, SOWT
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.
- James S. Coleman, “Social Capital in the Creation of Human Capital,” American Journal of Sociology (1988): S95–S120, http://www.jstor.org/stable/2780243.
- 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.
Also interesting (but we won't have time to discuss in class):
- 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.
- Alejandro Portes, “Social Capital: Its Origins and Applications in Modern Sociology,” Lesser, Eric L. Knowledge and Social Capital. Boston: Butterworth-Heinemann (2000): 43–67.
- Mark Granovetter, The Strength of Weak Ties: A Network Theory Revisited (JSTOR, 1981), http://www.jstor.org/stable/pdf/202051.pdf.
- 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.
- 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.
- 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.
Demography-specific:
Week 6 (2/27): Communities, social capital cont.
- Peter M. Blau, “A Macrosociological Theory of Social Structure,” American Journal of Sociology 83, no. 1 (1977): 26–54, http://www.journals.uchicago.edu/doi/abs/10.1086/226505.
- 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.
- 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.
Also interesting (but we won't have time to discuss in class):
- Jure Leskovec, Daniel Huttenlocher, and Jon Kleinberg, “Signed Networks in Social Media,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (ACM, 2010), 1361–1370, https://dl.acm.org/citation.cfm?id=1753532.
- 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 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.
- Laura Katherine Gee, Jason J. Jones, and Moira Burke, “Social Networks and Labor Markets: How Strong Ties Relate to Job Finding on Facebook’s Social Network” (2016), http://www.journals.uchicago.edu/doi/pdfplus/10.1086/686225.
- Peter J. Bickel and Aiyou Chen, “A Nonparametric View of Network Models and NewmanGirvan and Other Modularities,” Proceedings of the National Academy of Sciences 106, no. 50 (2009): 21068–21073, http://www.pnas.org/content/106/50/21068.full.
- Mark Granovetter, “Economic Action and Social Structure: The Problem of Embeddedness,” American Journal of Sociology (1985): 481–510, http://www.jstor.org/stable/2780199.
- 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.
- Sergio Currarini, Matthew O. Jackson, and Paolo Pin, “Identifying the Roles of Race-Based Choice and Chance in High School Friendship Network Formation,” Proceedings of the National Academy of Sciences 107, no. 11 (2010): 4857–4861, http://www.pnas.org/content/107/11/4857.short.
- Jukka-Pekka Onnela et al., “Geographic Constraints on Social Network Groups,” PLoS One 6, no. 4 (2011): e16939, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0016939.
Also interesting, but we will not have time to discuss:
- 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.
- Matthew O. Jackson and Brian W. Rogers, “Meeting Strangers and Friends of Friends: How Random Are Social Networks?” The American Economic Review 97, no. 3 (2007): 890–915, http://www.ingentaconnect.com/content/aea/aer/2007/00000097/00000003/art00015.
- Benjamin W. Domingue et al., “The Social Genome of Friends and Schoolmates in the National Longitudinal Study of Adolescent to Adult Health,” Proceedings of the National Academy of Sciences (2018): 201711803, http://www.pnas.org/content/early/2018/01/08/1711803115.short.
- 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.
- Anna D. Broido and Aaron Clauset, “Scale-Free Networks Are Rare,” arXiv:1801.03400 [Physics, Q-Bio, Stat] (January 2018), http://arxiv.org/abs/1801.03400.
- 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.
- 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.
Some recent online discussions of the power law debate (not required reading):
Also interesting (but we won't have time to discuss in class):
- The online textbook Network Science by Barabasi
- A. Clauset, C.R. Shalizi, and M.E.J. Newman, “Power-Law Distributions in Empirical Data,” arXiv:0706.1062 (2007), http://epubs.siam.org/doi/abs/10.1137/070710111.
- 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.
- 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.
- Abigail Z. Jacobs et al., “Assembling Thefacebook: Using Heterogeneity to Understand Online Social Network Assembly,” in Proceedings of the ACM Web Science Conference (ACM, 2015), 18, http://dl.acm.org/citation.cfm?id=2786477.
- 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.
- 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/.
- we'll have an in-class demo of breadboard. Bring your laptop!
- 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.
- 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.
- David G. Rand et al., “Static Network Structure Can Stabilize Human Cooperation,” Proceedings of the National Academy of Sciences 111, no. 48 (2014): 17093–17098, http://www.pnas.org/content/111/48/17093.short.
- Akihiro Nishi et al., “Inequality and Visibility of Wealth in Experimental Social Networks,” Nature 526, no. 7573 (2015): 426–429, http://www.nature.com/nature/journal/v526/n7573/abs/nature15392.html.
Also interesting, but we will not have time to discuss:
- 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.
- 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.
- 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.
- Matthew O. Jackson, Tomas Rodriguez-Barraquer, and Xu Tan, “Social Capital and Social Quilts: Network Patterns of Favor Exchange,” The American Economic Review 102, no. 5 (2012): 1857–1897, http://www.ingentaconnect.com/content/aea/aer/2012/00000102/00000005/art00004.
3/27: Spring break
Week 10 (4/3): Contagion and influence - simple contagion and epidemics; methodological challenges
- we'll finish our discussion of the papers from last time, along with a breadboard demo
- 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.
- (Skim) 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.
- David A Kim et al., “Social Network Targeting to Maximise Population Behaviour Change: A Cluster Randomised Controlled Trial,” The Lancet 386, no. 9989 (July 2015): 145–153.
Also interesting, but we will not have time to discuss:
- Shweta Bansal, Bryan T. Grenfell, and Lauren Ancel Meyers, “When Individual Behaviour Matters: Homogeneous and Network Models in Epidemiology,” Journal of the Royal Society Interface 4, no. 16 (2007): 879–891, http://rsif.royalsocietypublishing.org/content/4/16/879.short.
- Controversy over the C-F findings on the contagion of obesity (blog post by Andrew Gelman)
- 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.
- Social Contagion Theory: Examining Dynamic Social Networks and Human Behavior (a response to some criticisms of Christakis and Fowler)
- Matt J. Keeling et al., “Individual Identity and Movement Networks for Disease Metapopulations,” Proceedings of the National Academy of Sciences 107, no. 19 (2010): 8866–8870, http://www.pnas.org/content/107/19/8866.short.
- ABHIJIT BANERJEE et al., “Using Gossips to Spread Information: Theory and Evidence from a Randomized Controlled Trial” (2017), https://arxiv.org/pdf/1406.2293.pdf.
- 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.
- Stéphane Helleringer and Hans-Peter Kohler, “Sexual Network Structure and the Spread of HIV in Africa: Evidence from Likoma Island, Malawi:” AIDS 21, no. 17 (November 2007): 2323–2332.
- 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.
- 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.
- Marcel Salathé and James H. Jones, “Dynamics and Control of Diseases in Networks with Community Structure,” PLoS Comput Biol 6, no. 4 (2010): e1000736, http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000736.
4/10: PAA (no class)
Week 11 (4/17): Contagion and influence - complex contagion
- Mark Granovetter, “Threshold Models of Collective Behavior,” American Journal of Sociology (1978): 1420–1443, http://www.jstor.org/stable/2778111.
- 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.
- 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.
- 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.
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.
- 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.
- 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.
Especially relevant for demography:
Week 12 (4/24): Contagion and influence - peer effects
- We'll continue our discussion from last week
- Abhijit Banerjee et al., “The Diffusion of Microfinance,” Science 341, no. 6144 (2013): 1236498, http://science.sciencemag.org/content/341/6144/1236498.short.
- 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.
Also interesting, but we won't have time to discuss:
- Elizabeth Levy Paluck, Hana Shepherd, and Peter M. Aronow, “Changing Climates of Conflict: A Social Network Experiment in 56 Schools,” Proceedings of the National Academy of Sciences 113, no. 3 (2016): 566–571, http://www.pnas.org/content/113/3/566.short.
- 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.
- Bruce Sacerdote, Peer Effects with Random Assignment: Results for Dartmouth Roommates (National bureau of economic research, 2000), http://www.nber.org/papers/w7469.
- 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.
- 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.
- 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.
Week 13 (5/1): Mini-conference
Final paper due
Optional wrap-up readings (we won't discuss in class):
- 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.
- Matthew O. Jackson, Brian W. Rogers, and Yves Zenou, “The Economic Consequences of Social Network Structure” (2016), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2467812.
Religious Accommodations
Requests to accommodate a student's religious creed by scheduling tests or examinations at alternative times should be submitted directly to the instructor. Reasonable common sense, judgment and the pursuit of mutual goodwill should result in the positive resolution of scheduling conflicts. The regular campus appeals process applies if a mutually satisfactory arrangement cannot be achieved.
Statement on Academic Freedom
Both students and instructors have rights to academic freedom. Please respect the rights of others to express their points of view in the classroom.
DSP Accommodations
Please see the instructor to discuss accommodations for physical disabilities, medical disabilities and learning disabilities.
Student Resources
The Student Learning Center provides a wide range of resources to promote learning and academic success for students. For information regarding these services, please consult the Student Learning Center Website: https://slc.berkeley.edu/
Academic Integrity
The high academic standard at the University of California, Berkeley, is reflected in each degree that is awarded. As a result, every student is expected to maintain this high standard by ensuring that all academic work reflects unique ideas or properly attributes the ideas to the original sources.
These are some basic expectations of students with regards to academic integrity:
- Any work submitted should be your own individual thoughts, and should not have been submitted for credit in another course unless you have prior written permission to re-use it in this course from this instructor.
- All assignments must use "proper attribution," meaning that you have identified the original source and extent or words or ideas that you reproduce or use in your assignment. This includes drafts and homework assignments!
- If you are unclear about expectations, ask your instructor or GSI.
- Do not collaborate or work with other students on assignments or projects unless you have been given permission or instruction to do so.