14.15J | Spring 2018 | Undergraduate


Project Ideas

Project Ideas

Below is a list of project suggestions. These are merely examples and you are not required to do project from one of these topics. Use them as a “model” to potentially decide on your own project idea. Of course, you are welcome to utilize one of these topics as a project.

  1. Estimate a network optimization problem in an airline route network.
  2. Look at diffusion of ideas in patent citation data.
  3. Test homophily in a social network; look at different types of friendships and analyse interactions between them.
  4. Read two of the papers below on financial networks and contagion, and compare the approaches taken:
  5. Analyze Degroot learning by focusing on its differences from Bayesian Learning. This paper might be a good place to start:
  6. Analyze what export networks tell us about how countries grow and develop. Is the complexity measure reasonable? Is there a better measure of complexity you can come up with? As an extra empirical exercise, have a look at what import networks can tell you.
  7. Compare and contrast structural properties of different social networks. What are their common features? How do they differ?
  8. What is the structure of languages?
  9. Macroeconomics shocks: how do they spread? Review and contrast these papers:
  10. Simulate different types of epidemics in a number of (offline) social networks. Suggest prevention strategies given a fixed budget.  * Drakopoulos, Kimon, Asuman Ozdaglar, and John Tsitsiklis. “When Is a Network Epidemic Hard to Eliminate?Mathematics of Operations Research 42, no. 1 (2017): 1–14.
  11. Apply network centrality metrics on air traffic delay networks. Identify influencers in the network and provide recommendations on how to minimize air traffic delay. * Bureau of Transportation Statistics. “On-time Performance—Flight Delays at a Glance.” * Joint Economic Committee. “Your Flight Has Been Delayed Again.” US Senate. * Steele, Patrick Robert. “Understanding and Minimizing Flight Delay” (2010). College of William & Mary Undergraduate Honors Theses. Paper 702.
  12. What makes online content go viral? Review and contrast these papers: * Berger, Jonah and Katherine Milkman. “What Makes Online Content Viral?” SSRN, 2009. * Khosla, Aditya, Atish Das Sarma, and Raffay Hamid. “What Makes an Image Popular?” IW3C2, 2014.
  13. Download the street level traffic flow data for London (or another major city). Use data on capacity, distances (Google Maps) and speed limits to identify delays. Calculate the price of anarchy on London roads. * Traffic Counts of London * Youn, Hyejin, Michael Gastner, and Hawoong Jeong. “Price of Anarchy in Transportation Networks: Efficiency and Optimality Control.” Physical Review Letters (2010) 101.
  14. Consider all network datasets. What minimal set of network properties do you need to know in order to classify the type of a network? E.g. how can you tell a brain network from a Facebook network without seeing any labels?  * Network Repository
  15. Simulate different linear best-response game in different growing networks. When does a unique equilibrium exist? What are its properties? How does it change? Who are the key players? For a simulation of a coordination game in growing networks, see: * Tomassini, Marco and Enea Pestelacci. “Coordination Games on Dynamical Networks.” Games (2010).
  16. Analyze the data from memetracker. Can you identify any particular influencers? What is the structure of the network? Are there any similarities in memes/phrases that tend to be popular? * SNAP: Network Databases
  17. Pick a few different network metrics (centralities etc) and implement them on Apache Spark using RDDs or GraphFrames. Run these on large networks—how do different centralities differ in terms of performance, parallelizability, ease/difficulty of implementation?
  18. Analyze the US power grid network. Can you identify areas particularly vulnerable to black/brown outs? Does this network resemble any of the networks we studied?
  19. Build a meeting / scheduling system (like Doodle) that accepts preference for different options in terms of comparisons from people. * Negahban, Sahand, Sewoong Oh, and Devavrat Shah. “Rank Centrality: Ranking from Pairwise Companions.” Operations Research 65, no. 1 (2017): 266–287.
  20. Use / design comparison based ranking to potentially resolve controversy of NCAA football season 1990–91. * 1990–91 NCAA Football Bowl Games
  21. Analyze and obtain insights from the following data about connections of President (then candidate) Trump: * Astounding Complex Visualization Untangles Trump’s Business Ties
  22. Understand, utilize and explain “Granger Causality’.” * Granger, Clive. “Investigating Causal Relations by Econometric Models and Cross-spectral Methods.” Econometrica 37, no. 3 (1969): 424–438.

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