“Soulful” … “Catchy” … “Cool” … “Cheesy” … “Edgy”
How do people connect to and describe the music they have just heard?
EMI Insight performs extensive market research about their artists by interviewing thousands of people around the world. This research has produced EMI One Million Interview Dataset; one of the largest music preference datasets in the world today, that connects data about people–who they are, where they live, how they engage with music in their daily lives– with their opinions about EMI’s artists.
This Data Science London hackathon will focus on one key subset of this data: understanding what it is about people and artists that predicts how much people are going to like a particular track. We have taken a sample of the data from the United Kingdom that provides a granular mixture of profile, word-association, and rating data.
The goal of this weekend hackathon is to design an algorithm that combines users’ (a) demographics, (b) artist and track ratings, (c) answers to questions about their preferences for music, and (d) words that they use to describe EMI artists in order to predict how much they like tracks they have just heard.
There is also a Data Visualization track for data artists to show off their work.
Competition runs from 24 hours from Saturday, July 21st 1pm London – Sunday, July 22nd 1pm
Data will be made available 24 hours prior to the start of the contest (Hear that California? No waking up at 5am to access the dataset this time.)
Prizes sponsored by EMI and EMC/Greenplum
For more info on the origin of event http://musicdatascience.com/
? >registration for the on-site event.
Remote participation via Kaggle https://www.kaggle.com/c/MusicHackathon
Hashtags #musicdata #ds_ldn #DSGhack