What are more meaningful ways to discover music that is Christian?
Music is a universal language… How can we use sentiment analysis or other similar technologies to help us identify music that at its core invites people to worship, reflect and/or connect with God – whether or not it initially appears to be categorized as “Christian?”
The desired output for this challenge is discovery of new music that might not be normally classified as Christian. Teams should begin by determining alternate methods of mood and sentiment classification to produce more robust results. Solutions that are tested in alternate communities, languages or contexts are highly encouraged.
Testing on a large dataset (i.e. lots of test music) is important here and will support robust and sustainable solutions. Teams are encouraged to actively collaborate beyond their own city/native language and test/help improve each other’s solutions. It may be effective for different teams – including those who are pursuing their own approaches or solutions – to share research and data for the benefit of all.
It’s time to redefine “Christian music” in new and creative (yet Biblically-faithful) ways.
“Christian music” as it is today is only listened to by about 4 in 10 Millennials. While is allows for listeners’ moods to be improved, gives them a way to worship or enter into “time with God”, and helps them to tune out negativity, it also had some downfalls. It was also seen as non-relevant, cheesy, and repetitive. Some felt like it didn’t address the reality of their life and show the hard, messy parts of life. Some liked the idea of finding music by Christians versus “Christian Music”. While we know that music is a universal language, how can the strategies of Christian music be redefined to include more universal messages of betterment: love, forgiveness, kindness, joy, etc.
Data, APIs or Resources
Million Song Dataset: a freely-available collection of audio features and metadata for a million contemporary popular music tracks.
Natural Language Processing
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