A statistical analysis replicating key findings from "Why Civil Resistance Works" by Erica Chenoweth and Maria J. Stephan, investigating the effectiveness of nonviolent versus violent campaigns.
-
Historical Trends Analysis
- Frequency analysis of nonviolent vs violent campaigns by decade
- Success rate comparison between campaign types
- Visualization of campaign trends over time
-
Participation Analysis
- Investigation of the 3.5% rule
- Analysis of largest resistance campaigns (1946-2014)
- Statistical validation of participation thresholds
-
Statistical Modeling
- Logistic regression analysis of campaign success factors
- Control for population size and regime type
- Confidence interval analysis for success probability
- Clone the repository:
git clone https://github.com/marsidmali/Exploring-Why-Civil-Resistance-Works.git
cd Exploring-Why-Civil-Resistance-Works
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
Exploring-Why-Civil-Resistance-Works/
│
├── data/ # Dataset files
│ ├── NAVCO 1.2 Updated.xlsx
│ └── p5v2018.xls
│
├── notebooks/ # Jupyter notebooks
│ └── Exploring-Why-Civil-Resistance-Works.ipynb
│
├── requirements.txt # Dependencies
└── README.md # Documentation
- Launch Jupyter Notebook:
jupyter notebook
- Open
Exploring-Why-Civil-Resistance-Works.ipynb
- Run all cells to perform the analysis
This project is licensed under the MIT License - see the LICENSE file for details.