A Monte Carlo Simulator for Studying Information Diffusion in Social Networks modelled as Markov Chains
Arguments:
1st Argument: Number of Nodes in Graph 2nd Argument: filename
Results (digest average over 100 runs and raw data) will be stored in
results/filename results/raw_filename
Simulator.py - generates data for increasing number of messages (in multiples (1-6) of nodes on the graph) SimulatorProbExp.py - generates data for increasing probabilities that someone will change their mind (from 0.1 - 0.5) for 3*n messages (where n is the number of nodes in the graph) Timings.py - works out the average time for graph generation and analysis.
DTMCSN.py - contains the underlying functions for Discrete Time Markov Chain modelling and simulation of information diffusion. It is used by the other scripts.
The graphs* files in results are sample input files for using gnuplot to create graphs of data.