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👀 A whole new way to Wikipedia
#15 | Making data sexy is the easiest thing in the world
Are you one of those people who, like me, think data is sexy AF? Away to the stocks with you if you disagree.
I LOVE data, even the awful, boring spreadsheet kind. Something about the whole making sense of it all makes me so happy. In fact, my first WICA was a representation of wealth, or more correctly, where you stand on the Zero : OBSCENE wealth scale.
Today, it’s another one of my favourites – Notabilia. Created by Giovanni Luca Ciampaglia, Dario Taraborelli, and Moritz Stefaner, on the tenth anniversary of Wikipedia in 2011, Notabilia is a visualisation of the 100 most controversial articles on the platform earmarked for deletion.
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For those who’ve never used Wikipedia () it is a multilingual free online encyclopedia written and maintained by a veritable army of volunteers. Every day thousands of new entries are added, of which a significant number fail Wikipedia’s inclusion standards. Wikipedia’s goal to cover the sum of all human knowledge often makes it hard to decide whether the content should be deleted or not. Enter Articles for Deletion, or AfD.
“We analysed and visualised Article for Deletion (AfD) discussions in the English Wikipedia,” the makers explain. “Each time a user joins an AfD discussion and recommends to keep, merge, or redirect the article a green segment leaning towards the left is added. Each time a user recommends to delete the article, a red segment leaning towards the right is added.”
The visualisation is a glorious whorly swirl of curly and straight lines that could be an artist’s rendition of a hibiscus flower or a toddler’s approximation of one. If you look closely, you’ll see that the most controversial subjects follow a straight line. The swirls are the conversations where all parties agree. The threads are clickable and take you to the actual discussion pages. I’ve been fascinated by this project since I first discovered it – it is magnificent and thought-provoking.
Let me know what you think? Better still, send me our favourite visual representation of data. I showed you mine, now show me yours.