Hua Xiao and Lingfei Wu
The emotional arousal and pleasure during music listening is a widely observed phenomenon but the mechanism behind it remained unsolved. We propose that the emotional effect of a song is relevant to the information it carries. In particular, a balance between pattern repeating and breaking should be achieved. This is because either zero-information (boring pattern repeated endlessly) or information-overload (Non-repeating patterns) is unacceptable to audience, although the optimum between these two extremes may vary among different audience. In the current study we use networks to represent the structure of songs. In these networks nodes are repeating units and edges are time intervals between them. We analyze the hierarchy of these networks and propose a novel index N to quantify the novelty (symmetry-breaking) of songs. This metric is a fingerprint for unique personal music taste across genres and thus is an important feature to be included in personalized music recommendation.