People have the ability to perceive emotion in music.
Certain types of music can express sadness or joy and may influence people's mood. Which musical features are more commonly associated with which emotions?
The conceptual basis for this project arises in the attempt to understand if data may contain emotional subjective information, by being connected. If we visualize music as a cultural barometer, generally somewhat subversive, the analysis of these emotions may constitute an unusual way of looking at music history.
Musicmoods is a dinamic data visualization project which uses the last.fm API to explore relations between moods and musical genres. It becomes an emotional analysis of society through music, during a given time and within the universe of the Last.FM users. It makes use of the number of track taggings, according to some moods and musical genres. Part of the user generated tags at Last.FM, such as happy and sad, are used to establish correspondences between feelings and songs. The top tagged tracks for each mood are displayed and classified by genre. The number of tracks displayed for each mood is chosen according to relative mood tagging. For each genre, the distribution over moods of these tracks are shown.
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