Mining Microblogs to Infer Music Artist Similarity and Cultural Listening Patterns
Sprache des Vortragstitels:
Englisch
Original Kurzfassung:
This paper aims at leveraging microblogs to address two
challenges in music information retrieval (MIR), similarity
estimation between music artists and inferring typical lis-
tening patterns at different granularity levels (city, country,
global). From two collections of several million microblogs,
which we gathered over ten months, music-related information
is extracted and statistically analyzed. We propose
and evaluate four co-occurrence-based methods to compute
artist similarity scores. Moreover, we derive and analyze
culture-specific music listening patterns to investigate the
diversity of listening behavior around the world.