improving music mood classification using lyrics, audio and social tags

in today’s music listening environment. Hence, the MIR experiments using four mood categories
based on Russell’s model have been trying to solve part of the real problem, but not even close to
the complete problem. However, let us recall that Russell’s model is a dimensional model instead
of a categorical one, and thus it can be extended to include more adjectives. In fact, later studies
have extended this model in many different ways (Schubert, 1996; Thayer, 1989; Tyler, 1996). It
is possible that many, if not all, tags in the derived categories could find their places in the twodimensional
space, but it is a topic beyond the scope of this dissertation.
3.3.3 Distances between Categories
Both Hevner’s circle and Russell’s space demonstrate relative distances between moods. For
instance, in Russell’s space, “sad” and “happy,” “calm” and “angry” are at opposite places while
“happy” and “glad” are close to each other.
To see if there are similar patterns in the derived categories, the distances between the
categories were calculated according to the co-occurrences of artists associated with the tags.
The last.fm API provides the top 50 artists associated with each tag, and thus the top artists for
each of the 136 tags in the derived categories were collected, and then the distances between the
categories were calculated based on artist co-occurrences. Figure 3.3 shows the distances of the
sets of categories plotted in a two-dimensional space using Multidimensional Scaling (Borg &
Groenen, 2004). In this figure, each category is represented by one tag in this category and a
bubble whose size is proportional to the total times for which the tags in this category are used.
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