We present results of text data mining experiments for music retrieval, analyzing microblogs gathered from November 2011 to September 2012 to infer
music listening patterns
all around the world. We assess
relationships between particular music preferences and spatial properties
, such as month, weekday, and country, and the
temporal stability of listening activities
. The findings of our study will help improve music retrieval and recommendation systems in that it will allow to incorporate geospatial and cultural information into models for music retrieval, which has not been looked into before.