This week I worked on understanding the influence of all nodes in a network and efficient collective influence maximization in cascading processes with first-order transitions. I read a paper called “Understanding the Spreading Power of all Nodes in a Network: a Continuous-Time Perspective” by Glenn Lawyer. The paper talked about the correlation to epidemic outcomes, weighted graphs, and different networks. Here is a picture that shows and explains a network of nodes:
I also found a Python code on GitHub that will calculate PageRank. Next week I plan on installing NumPy, reading a paper on collective influence, and studying the PageRank code.