Exploring the Emotional Landscape of Music: An Analysis of Valence Trends and Genre Variations in Spotify Music Data

The objectives of this research are as follows. First, we employ a suite of regression models, including linear regression, support vector regression, This paper conducts an intricate analysis of random forest regression, and ridge regression, to musical emotions and trends using Spotify music predict valence scores based on the extracted audio data, encompassing audio features and valence attributes. By evaluating the performance of each scores extracted through the Spotipi API. Employing model, we discern their effectiveness in capturing the regression modeling, temporal analysis, mood intricate emotional nuances embedded within the transitions, and genre investigation, the study audio data.