# CS 765: Complex Networks

## Due on Wednesday Sep 7 at 11:00 am

Network Basics (3 points)

Go to the site http://www.visualcomplexity.com. Select and list two projects describing a network. Answer the following about them (this may require going into the source web-page for the project, linked to from the visualcomplexity site).

1. What do the nodes and edges represent?
2. Is the graph directed? Weighted?
3. Can the data be represented as a bipartite graph?

Bipartite Graphs (7 points)

For this part, you may look at Pajek tutorial.

• Open it in Pajek by either clicking on the yellow folder icon under the word "Network" or by selecting File>Network>Read from the main menu panel.
• A report window should pop up confirming that the graph has been read and the filename and location will be displayed in the 'active' position of the network dropdown list.
• This is a 2 mode network containing two classes of nodes, actors and movies. Create a 2-mode partition (Net>Partition>2-Mode).
• Visualize the network using Pajek's Draw>Draw-Partition command from the main menu panel. The two classes of nodes should be colored differently.
• If labels are not shown, add them (Options>Mark Vertices Using>Labels).
1. Select from the draw toolbar a layout algorithm under 'Layout>'. Apply your favorite layout algorithm. Include an image.
2. Transform the network into a one-mode network (Net>Transform>2-Mode to 1-Mode>Rows). Draw the network (Draw>Draw). Include an image.
3. Qualitatively compare the structure of the 2-Mode to the 1-Mode network. Is there a loss of information?
4. Show the weights on each edge using (Options>Lines>Mark Lines>with Values). What do the values represent?
5. Compute the un-weighted degree of each node (Net>Partitions>Degree>All). Next draw the network using (Draw>Draw-vector). How is the degree represented?
6. Add the vector value to each vertex (it will be the degree/(max possible degree)) (Options>Mark Vertices Using>Vector Values). Include an image.
7. Who are the most important actors using this measure?
8. How does the boundary of the network (i.e. who is included) affect who is found to be most central?
9. Load the file actorsandmoviesWithGere.net. It contains one extra actor, Richard Gere. Repeat the above procedure.
10. In the 1-mode network of actors, is there a change in who is most central?
11. What does this tell you about biases and boundaries in sample selection?
12. Remove all edges between actors who have co-starred in fewer than 3 movies (Net>Transform>Remove>Lines with value>Lower than). Which actors comprise the central core of this network?