# A Graph-structured Dataset for Wikipedia Research

## TL;DR

This paper introduces a graph-structured dataset for Wikipedia that enables efficient access and filtering of Wikipedia subnetworks, facilitating research in language, social behavior, and network theory.

## Contribution

The authors present a novel graph-based data structure and tools that improve access to Wikipedia subnetworks, addressing the challenge of large dataset processing for researchers.

## Key findings

- Efficient retrieval of Wikipedia subgraphs using the proposed data structure.
- Tools for filtering viewership statistics of Wikipedia pages.
- Dataset available for research on Wikipedia's network structure.

## Abstract

Wikipedia is a rich and invaluable source of information. Its central place on the Web makes it a particularly interesting object of study for scientists. Researchers from different domains used various complex datasets related to Wikipedia to study language, social behavior, knowledge organization, and network theory. While being a scientific treasure, the large size of the dataset hinders pre-processing and may be a challenging obstacle for potential new studies. This issue is particularly acute in scientific domains where researchers may not be technically and data processing savvy. On one hand, the size of Wikipedia dumps is large. It makes the parsing and extraction of relevant information cumbersome. On the other hand, the API is straightforward to use but restricted to a relatively small number of requests. The middle ground is at the mesoscopic scale when researchers need a subset of Wikipedia ranging from thousands to hundreds of thousands of pages but there exists no efficient solution at this scale. In this work, we propose an efficient data structure to make requests and access subnetworks of Wikipedia pages and categories. We provide convenient tools for accessing and filtering viewership statistics or "pagecounts" of Wikipedia web pages. The dataset organization leverages principles of graph databases that allows rapid and intuitive access to subgraphs of Wikipedia articles and categories. The dataset and deployment guidelines are available on the LTS2 website \url{https://lts2.epfl.ch/Datasets/Wikipedia/}.