Wikimedia Edits and Editors by Country

Overview

This project provides a Jupyter Notebook that visualizes the edits and editors of Wikimedia projects for a country of a choice. The data is sourced directly from the Wikimedia Foundation and has been processed to maintain privacy through differential privacy techniques. You can find more information about the dataset here.

The initial set-up was done by HTriedman (WMF), and you can find the example here.

The data is grouped into three user levels based on the number of edits made within a given period (either monthly or weekly):

• 1-4 edits : Users who make between 1 and 4 edits.
• 5-99 edits : Users who make between 5 and 99 edits.
• 100 or more edits : Users who make 100 or more edits.

Features

• Visualization : Instantaneous plots showcasing edits and editors for English Wikipedia, Spanish Wikipedia, Wikimedia Commons, and Wikidata.
• Country-specific Data : Easily adjustable to view data for different countries.
• Data Frequency : Choice between monthly or weekly data representation.

Getting Started

Prerequisites

• Python 3.x
• Jupyter Notebook
• Pandas
• Matplotlib
• Requests
• Seaborn

Installation

You can either download the monthly or weekly code and run it locally on your computer with a code editor. Or you can use an online Notebook, for example PAWS.

Usage

1. Open the geoeditors_monthly.ipynb or the geoeditors_weekly.ipynb in a Jupyter Notebook.
2. Adjust the country variable to your desired country.
3. Run the notebook to generate visualizations.

For example, for Spanish Wikipedia, you'll see the following sections:

• Editors Section : This section contains data about the number of editors, segmented by user levels.
• Edits Section : This section provides detailed data and visualizations of the edits.

First, you'll see a table with the raw data, followed by plots that visualize the edit patterns over time.

Steps in Detail

1.Open the Notebook :

• Launch Jupyter Notebook and open geoeditors_monthly.ipynb or thegeoeditors_weekly.ipynb .

2. Adjust Country Variable :

• Locate the cell where the country variable is defined.
• Change the country name to the one you are interested in (e.g., country = "Chile").
• You have to choose from the ISO alpha-2 codes.

3. Run the Notebook :

• Execute the cells in the notebook sequentially.
• The notebook will process the data and generate visualizations accordingly.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the GNU General Public License v3.0. See LICENSE for more details.

Acknowledgments

• Data sourced from the Wikimedia Foundation.
• Inspiration and initial structure from the provided example by HTriedman (WMF).