Analysis of Wikipedia Editorial Activities

Repository Overview

This repository contains the code for a project completed as part of my MSc course. It demonstrates my intermediate coding skills and provides an overview of the work I undertook during the program.

Project Overview

The goal of this project is to analyze editorial activities on Wikipedia, such as creating, editing, and reverting articles. By examining these activities, the project aims to understand the dynamics of human interaction and behavior on online platforms. The project is inspired by research studies focusing on online editorial activities, networks, and communities within Wikipedia.

Relevant Research Studies:

• Tsvetkova, M., García-Gavilanes, R., Floridi, L., & Yasseri, T. (2017). Even good bots fight: The case of Wikipedia. PLoS ONE, 12(2), e0171774.
• Gildersleve, P., Lambiotte, R., & Yasseri, T. (2023). Between news and history: identifying networked topics of collective attention on Wikipedia. Journal of Computational Social Science, 6(2), 845-875.

Code Structure

• analysis.ipynb: Jupyter notebook containing the final output of the analysis.
• /data_loading.py: Module to load and clean the data for analysis.
• /data_analysis.py: Module for identifying mutual reverts and calculating the similarity of edit activities.
• /visualization.py: Module for visualizing the results of the analysis.

Notes

• The code is designed to address specific problems and cannot be shared publicly. However, the code notes have been converted to markdown to provide a general overview of the task.
• The repository does not contain data provided by the school, as sharing such data is not permitted.
• For this project, only basic Python modules such as pickle, random, datetime, and libraries like numpy, matplotlib, and seaborn are used. Advanced data processing libraries like pandas, networkx, and scikit-learn were not permitted for use in this project to encourage module writing.