A Graph-structured Dataset for Wikipedia Research

03/20/2019
by   Nicolas Aspert, et al.
0

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 <https://lts2.epfl.ch/Datasets/Wikipedia/>.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/25/2022

Wikinformetrics: Construction and description of an open Wikipedia knowledge graph dataset for informetric purposes

Wikipedia is one of the most visited websites in the world and is also a...
research
02/17/2020

What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions

In this work, we propose an automatic evaluation and comparison of the b...
research
03/11/2020

Entity Extraction from Wikipedia List Pages

When it comes to factual knowledge about a wide range of domains, Wikipe...
research
01/14/2017

Hedera: Scalable Indexing and Exploring Entities in Wikipedia Revision History

Much of work in semantic web relying on Wikipedia as the main source of ...
research
04/24/2017

Recognizing Descriptive Wikipedia Categories for Historical Figures

Wikipedia is a useful knowledge source that benefits many applications i...
research
04/12/2019

Female scholars need to achieve more for equal public recognition

Different kinds of "gender gap" have been reported in different walks of...
research
10/28/2020

A general method for estimating the prevalence of Influenza-Like-Symptoms with Wikipedia data

Influenza is an acute respiratory seasonal disease that affects millions...

Please sign up or login with your details

Forgot password? Click here to reset