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-toollibrary, 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
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Clone the repository:
git clone https://github.com/lgomezt/Analysis-of-Tweets-During-the-2021-Social-Unrest.git
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Navigate to the Tutorials folder:
cd Analysis-of-Tweets-During-the-2021-Social-Unrest/TutorialsFollow the setup guides to prepare your environment.
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Install Requirements:
cd Analysis-of-Tweets-During-the-2021-Social-Unrest pip install -r requirements.txtInstall the necessary Python packages specified in requirements.txt.
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Navigate to the Code folder:
cd ../CodeRun the Jupyter notebooks in the following order.
- Save_tweets.ipynb
- Political Labelling.ipynb
- Retweet Adjacency Matrices.ipynb
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Check Results: After successfully running the code, you can examine the
Resultsfolder for the output.