Project shows Wikipedia changes in real-time

May 13, 2013
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Project shows Wikipedia changes in real-time

Wikipedia allows users to check out edits made to an article via its accompanying history page, which lists changes along with the date and time, IP address or username, and an edit summary. Such is a useful feature, providing essential information to the crowd-created and updated online encyclopedia. It doesn't, however, make it simple to see the big picture, and that is what two developers have partly changed via their open source project.

The project displays a global map, and updates in real-time when a change is made on Wikipedia, displaying it as a small circle that flashes on the editor's location, as well as the name of the article that was revised and the editor's IP address. Below the map is a scrolling text box containing more information, including a link to the article, the language of the article, and the city, state, and country where the edit was made.

So far, edits made on the English, Japanese, Russian, German, Spanish, Indonesian, and French Wikipedias are available, with users being able to select one or more to view. When watching the map under the English version of the website, it averaged about 500 edits per 33 seconds. While the edits shown are substantial, the project only tracks those made by unregistered users, which represent about 15-percent of the edits made to the online encyclopedia. The information is pulled via live feeds broadcast with Wikimon.

The programmers behind the project advise that, according to a survey done in 2007, edits made by unregistered users on Wikipedia are often of less value than ones made by registered users, advising that you can correct an issue if you happen to spot one while using their real-time visualization. The project was built using DataMaps, d3, and other services and libraries, and is open source for anyone to grab on github.

Watching the map provides an interesting passive sort of observation, giving us a peek into what articles are of interest to users and where those users are located. When observed long enough, shifts can be noticed, such as edits increasing and decreasing with the fluctuations of waking and working hours, topic trends, and more.

SOURCE: Hatnote


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