It’s been a little quiet on the Hatnote blog since the launch of RCMap, but today’s post puts an end to that. After a recent NPR/TED broadcast on the nature of collaboration gave a voice to real-time editing, we couldn’t help but try it out, too.
So, without further ado, Listen to Wikipedia. (Tune your speakers/headphones accordingly.)
Bells are additions, strings are subtractions. There’s something reassuring about knowing that every user makes a noise, every edit has a voice in the roar. (Green circles are anonymous edits and purple circles are bots. White circles are brought to you by Registered Users Like You.)
Apart from being a hopefully-pleasant audiation, Listen to Wikipedia (L2W) also addresses a couple other inquiries we’ve gotten more than a few times:
- Whereas RCMap only displays anonymous edits, L2W presents all edits to the main namespace in real time, with special handling for new-user signups for good measure.
- L2W uses color a bit differently, too. By making edits from unregistered/anonymous users green, and edits from user-driven bots purple, we hoped to give a relative visual sense of traffic from those sources. (Spoiler alert: anon/bot edits represent less than a fifth of total edit traffic. L2W is a lot more active than RCMap.)
- Finally, because it used a world’s worth of border data, RCMap was a fairly heavy application. L2W’s more abstract approach to visualization should provide a lighter touch suitable for resource-constrained environments.
Listen to Wikipedia was written by Stephen LaPorte and Mahmoud Hashemi, and is open-source. Like RCMap, L2W gets its real-time Wikipedia data as broadcast by Wikimon. L2W was inspired by and partially based on Listen to Bitcoin, but was mostly rebuilt to use D3.js (also like RCMap). We also use howler.js for cross-browser audio support, and additional sound processing was facilitated by SoX.
We hope you enjoy listening to L2W as much as we enjoyed building it. Now, let’s go make some noise.
—Stephen and Mahmoud