1 min read
on Feb 10, 2015
How to collect data from the Twitter firehose Spotify stream, then analyze and publish that data to a real-time, live-updating visualization dashboard.

The Twitter firehose is an amazing way to stream Twitter data at real-time speed. What we can do with that data, well, that's entirely up to us.

In our previous Twitter firehose tutorial, we showed you how to analyze tweet streams for emotions, then analyze and visualize that data on a live updating, real-time map.

Why stop there? Onto the next tutorial!

In this tutorial, we took a Twitter stream that included a list of Spotify albums that are being listened to. To visualize this, we made an ambient background (much like the iTunes album artwork screensaver), where the latest album being listened to is collected and published:

spotify twitter firehose stream data visualization

With PubNub, we can skip the complicated process of long polling and write the front-end code with JavaScript. This way you can send and receive JSON data, and with our new real-time Twitter firehose stream, you can consume and turn this public data into visualizations.

You can check out the live version of the application here, and the source code here.

Want to build it yourself? Head over to the Twitter Developer Blog, where we wrote a full tutorial on building a Spotify Twitter Stream Visualization. The tutorial includes an introduction to the Twitter Firehose API, a comprehensive code walkthrough and tutorial, and an Embedly tutorial as well.

Data Firehose Resources

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