CSS-Project

Github for project Complex System Simulation.

This project studies a network model of belief dynamics to understand how interactions lead to consensus or fragmentation. We simulate the model and analyze community sizes as system parameters are varied.

Library structure

Module / Folder	Purpose
base_model.py	Core belief-dynamics models (homogeneous and heterogeneous variants)
run_experiments.py	Runs simulations to generate p(s) distributions and data collapse
Critical_fraction.py	Computes and plots max community size and consensus size vs mediator fraction
helpers.py	Serves as the mathematical engine for analysis and handling statistical tasks
plot_experiments.py	Visualization of p(s) distributions and data collapse results
Extras/	Contains Roza's initial alternate test version of the base model, unused because we continued with better base_model.py, but included for the sake of contributions. Also it contains the extension of base model to include social media influence but unused because of lack of time.
Complex Systems Presentation.pptx	Power point presentation
data/	Stored data file
figures/	Containts the generated figures for analysis

Requirements

This package is written in Python 3 and requires the following packages:

• numpy
• networkx
• scipy
• zlib
• powerlaw

Optional (for plotting and saving results)

• matplotlib
• csv (part of the Python standard library)

References

• Coevolving networks: P. Holme & M. E. Newman, Nonequilibrium phase transition in the coevolution of networks and opinions, Phys. Rev. E 74, 056108 (2006).