In this project, we analyze the evolution of various segregation metrics during the "Social Outburst of Colombia" in 2021.
To accomplish this, we collected over X million tweets for three distinct periods:
- Regional elections prior to the Social Outburst (October 2019).
- Three months preceding the Social Outburst (January 2021).
- The Social Outburst in Colombia (April 28th to June 29th, 2021).
The repository is organized into three main folders:
- Code: Houses the Jupyter notebooks needed for data analysis and other computational tasks.
- Results: Contains the outputs from the analyses, such as graphs, CSV files, etc.
- Tutorials: Provides step-by-step instructions for setting up your environment and installing dependencies.
The Tutorials
folder includes markdown files that guide you through the initial setup:
- 0. VM Setup.md: Instructions for setting up a Virtual Machine to run the project.
- 1. Create venv.md: A guide for creating a Python virtual environment to isolate the project's dependencies.
- 2. Install graph-tool.md: Instructions for installing the
graph-tool
library, which is essential for this project.
The Code
folder contains all the Jupyter notebooks necessary for the analysis. For a more detailed explanation of the project's pipeline, refer to Code Directory.
The Results
folder includes all the output generated from the Jupyter notebooks in the Code
folder. This can include, but is not limited to:
- CSV files
- Graphs and plots
- Model checkpoints
-
Clone the repository:
git clone https://github.com/lgomezt/Analysis-of-Tweets-During-the-2021-Social-Unrest.git
-
Navigate to the Tutorials folder:
cd Analysis-of-Tweets-During-the-2021-Social-Unrest/Tutorials
Follow the setup guides to prepare your environment.
-
Install Requirements:
cd Analysis-of-Tweets-During-the-2021-Social-Unrest pip install -r requirements.txt
Install the necessary Python packages specified in requirements.txt.
-
Navigate to the Code folder:
cd ../Code
Run the Jupyter notebooks in the following order.
- Save_tweets.ipynb
- Political Labelling.ipynb
- Retweet Adjacency Matrices.ipynb
-
Check Results: After successfully running the code, you can examine the
Results
folder for the output.