improving music mood classification using lyrics, audio and social tags

5.2.2 Selecting Songs
The next step is to select positive and negative examples for each of the 18 categories. The
general idea is that if a song is frequently tagged with a term in a category, it should be selected
as a positive example for that category. On the other hand, if a song is never tagged with any
term in a category, but at the same time is heavily tagged with other tags (mood-related or not),
then it should be taken as a negative example for the category. Therefore, the frequency or count
of the social tags is crucial for this step.
5.2.2.1 Tag Count on Last.Fm
The last.fm API provides the 100 most popular tags applied to each song and the number of
times each tag is applied to this song (called “count” thereafter). To date, the API only provides
normalized tag counts instead of real, absolute counts. For each song, the most popular tag gets
count 100, and other tags get integer numbers between 0 and 100 proportional to the count of the
most popular tag. Tags with count 0 are those appearing too few times compared to other tags
associated to a song.
In selecting songs for these categories, one should avoid songs that are only tagged with a
term by accident or worse, by mistake or mischief. Ideally, one should select songs with high
counts. However, with only the normalized tag counts available, there is no way to calculate the
real, absolute tag counts. Hence, a heuristic is used to ensure a tag is picked up for a song only
when it has been applied to this song for, at the very least, more than once. Only songs satisfying
one of the following conditions were counted as candidate positive songs in a category:
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