What you are about to see is a graphical representation of the English Wikipedia where each circle represents an article.
The size of a circle depends on how many user pageviews it got on a particular month. For example you will see that the Main Page article is the biggest one as it gets the most views.
The placement of the articles is based on the links between them. The more closely linked the two articles are, the closer they should appear. The current algorithm for the placement of the circles is naive, includes randomness and is not totally accurate.
Select the size of the Wikipedia map you'd like to explore. The larger the dataset you choose, the more accurate the placement will be.
I highly recommend using a laptop / desktop for the best experience.
Due to the nature of Wikipedia, the dataset contains NSFW elements.
The dataset is from January 2026, thus the placement might differ from the current state of Wikipedia, also the dataset may contain errors.
The placement of the articles is naive, you might see some articles wildly out of place.
An example of this is the Twitter article. Although you would expect it to be near other social media apps, it is near anime communities. The reason for this is that anime articles have links to Twitter in their reference section. Many anime news come from Twitter which means that nearly every anime article has a link to the Twitter article on Wikipedia. This makes Twitter appear very close to anime communities. This will be improved in the next iteration.
If on desktop / laptop use your mouse / touchpad to pan and scroll. For touchpad, scroll by dragging two fingers. Click on articles to see the wiki page.
If on mobile use one finger to pan around and pinch with two fingers to zoom in / out. Clicking articles is disabled on mobile.
Data is collected from Wikimedia dumps
Uses Leiden algorithm for community detection and to build the graph itself
WebGL (Three.js) with instanced rendering + troika-three-text