What it does

After the Music Hack Day, this hack has been improved, the current version is at while the original version can stil be found at

It takes what people all over the world are posting on Twitter with the hashtag #nowplaying (last 500 tweets) and tries to extract the artists played using some heuristics.

Using artist similarities measures (Universal APIs) it computes a target artist that would be a good compromise for the music tastes of the people, in that moment, considering what they posted on the last 500 tweets.

It plays a TOP song by this target artist (Spotify APIs) and at the end of the song the process re-starts, analyzing again the last 500 tweets, computing the target artist and playing a song.

At the same time, every two seconds a graph representing the "world beat" is refreshed: the app shows an equalizer representing the mix of genres/styles played in that moment and the inferred people aggregated mood. The aggregated mood is computed assuming that people play a more lively song when they are in a good mood and it's computed using the valence [1] audio feature provided by the Spotify APIs for the song played by the radio.

[1] A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry). See link

How I built it

Challenges I ran into

Accomplishments that I'm proud of

What I learned

What's next for The World Beat

Share this project: