information diffusion

  • epidemics
  • information diffusion
  • viral marketing
  • temporal networks

Team

Scott, Kieraj, Bianca, Alex, Brendan, Brenda

Project

Computing tasks:
1. Read Goel’s paper (click on name)
3. Implement Goel’s threshold model
4. Import data into MATLAB (or alternative SW)
– Get the data from here: http://snap.stanford.edu/data/twitter_combined.txt.gz
– Build an directed graph (for now) using the columns of the text file
5. Extract a subgraph of 1,000 nodes using BFS
6. Run threshold models in the subgraph for different threshold values and compare the results

Policy tasks:
1. Read Chapter 4 of “Everything is Obvious–Once you Know the Answer”
2. Think about network properties that facilitate cascades

COMM students: have a look at the questions listed in this document and try to articulate a paragraph-long answer to them. Submit your answers to the blog.

NETS students: due on Friday, April 3
1. Read and review the following papers:
a. https://5harad.com/papers/diffusion.pdf
b. “Identification of Influencial Spreaders in Complex Networks” by Kitsak
et al. in Nature 2010.
2. In the following steps, you need to use the network imported in Phase I.
3. Design a seeding strategy to spread information based on the following criteria:
a. Largest degrees
b. Eigenvector centrality
c. k-core decomposition (see Kitsak’s paper).
d. Cascading size (to be covered in class)
4. Code algorithms to implement each one of the above criteria:
a. Run your algorithms in the network extracted in Phase I
b. Use a number of seeds that varies from 1 to 20
c. Compare the effectiveness of each strategy

Due on Friday April 10.
All the students in the group should collaborate to solve the tasks below.
1. Code an algorithm to classify and count different types of cascades
2. Study the changes in the frequencies of each type of cascade as you tune the spreading parameters
3. Can you explain these results?
Due on Friday April 17.
All the students in the group should collaborate to solve the tasks below.
1. Consider other spreading criteria to increase influence
2. If you are the owner of the network and you want to maximize the spread of information, how would you modify the network? i.e. Cut links, rewire connections, etc.
3. If you wanted to contain the spread of information in the network, how would you modify the structure of connections? Think about scenarios where this would be a legitimate goal.
You should prepare, as a group, a slide show and present your work in class on Friday April 24. The presentation should be less than 20 minutes long. Send the slides to Josh (email below) no later than Thursday April 23!

Do not forget to update the blog with your advances! You will have to register your email the first time you post. If you have any figures, send them to Joshua Becker: jbecker[at]asc.upenn.edu. We will add them to the projects portfolio!

white_rectangle
figures
white_rectangle

Sandra Bailoninformation diffusion