Using Graph Clustering to Analyze the Spread of an Infectious Disease on a Random Large Social Network Graph
Term of Award
Master of Science in Mathematics (M.S.)
Document Type and Release Option
Thesis (restricted to Georgia Southern)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department of Mathematical Sciences
Committee Member 1
Committee Member 2
The purpose of this work is to analyze the spread of an infectious disease on a random large social network graph. The goal is to determine if graph clustering techniques are a viable option to reduce workload of analyzing of a large data set. A random graph generator was developed using characteristics from the Forest Fire Model. We then use this graph to model the spread of an infectious disease. We develop a preliminary trivial reduction method in which to use as a baseline to formulate and compare more efficient reduction methods. The use of basic statistics ensures the reductions mirror the spread of the disease on our initial random large social network graph.
Morley, Patrick R., "Using Graph Clustering to Analyze the Spread of an Infectious Disease on a Random Large Social Network Graph" (2015). Electronic Theses and Dissertations. 1314.