Algorithmic recommendations inaccurate for some music lovers
The HinduAlgorithms help users search, sort and filter music from range of collections. But the suggestions may be inaccurate for fans of non-mainstream music like pop and hard rock, according to a study titled ‘Support the underground: characteristics of beyond-mainstream music listeners’ by the Graz University of Technology in Austria. The team of researchers used a dataset containing listening histories of 4,148 users of the music streaming platform Last.fm who listened mostly to non-mainstream music or mostly mainstream music. They noticed the algorithm categorised music listeners into four main types: listeners of genres with only acoustic instruments like folk, users of high-energy music like hard rock and pop, users of music with no acoustics and no vocals like ambient music, and listeners of high-energy music with no vocals like electronica. This indicated a bias in music recommendation algorithm, with listeners of high-energy music receiving the least accurate music recommendations and those who mainly listened to ambient music.
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