improving music mood classification using lyrics, audio and social tags

CHAPTER 9: CONCLUSIONS AND FUTURE RESEARCH
9.1 CONCLUSIONS
Music mood is a newly emerging metadata type for music. Information scientists and
researchers in the MIR community have a lot to learn from music psychology literature, from
basic terminology to music mood categories. This research reviewed seminal works in the long
history of music psychological studies on music and mood, and summarized fundamental points
of view and their important implications for MIR research.
Social tags are a rich resource for exploring users’ perspectives. As mood categories in
music psychological models might lack the social context of today’s music listening
environment, this research derived a set of mood categories from social tags using linguistic
resources and human expertise. The resultant mood categories were compared to two
representative models in music psychology. The results show there were common grounds
between theoretical models and categories derived from empirical music listening data in real
life. While the mood categories identified from social tags could still be partially supported by
classic psychological models, they were more comprehensive and are more closely connected
with the reality of music listening. There are two principal conclusions. First, if handled
properly, social tags can be used to identify a set of reasonable mood categories that can both be
supported by classical theories and reflect the reality of music listening. Second, theoretical
models need to be modified to better fit today’s reality. This research exemplifies an approach of
using empirical data to refine and adapt theoretical models to better fit the reality of users’
information behaviors.
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