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improving music mood classification using lyrics, audio and social tags

improving music mood classification using lyrics, audio and social tags

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Figure 3.3 Distances of the 36 derived <strong>mood</strong> categories based on artist co-occurrences<br />

As shown in Figure 3.3, categories that are intuitively close (e.g., those denoted by “glad,”<br />

“cheerful,” “gleeful”) are positioned together, while those placed at almost opposite positions<br />

indeed represent contrasting <strong>mood</strong>s (e.g., the ones denoted as “aggressive” <strong>and</strong> “calm,”<br />

“cheerful” <strong>and</strong> “sad”). This evidences that the <strong>mood</strong> categories derived from <strong>social</strong> <strong>tags</strong> have<br />

similar patterns of category distances to those in psychological <strong>mood</strong> models. More interestingly,<br />

Figure 3.3 also shows the valence <strong>and</strong> arousal dimensions as those in Russell’s model. The<br />

horizontal dimension is similar to valence, indicating positive or negative feelings, while the<br />

vertical dimension is similar to arousal, indicating active or passive states of being. Finally, an<br />

interesting observation from the sizes of the bubbles is that <strong>tags</strong> reflecting sad feelings (e.g.,<br />

“sad” <strong>and</strong> “gloomy”) are much more frequently applied than those reflecting happy feelings<br />

(e.g., “glad” <strong>and</strong> “cheerful”).<br />

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