Алгоритм передбачення змін у кількості прослуховувань артистів на основі їх останніх дій

Abstract

This work delves into the development of a predictive algorithm designed to forecast changes in the number of artist listens based on their recent actions, considering their performance style. By analyzing patterns in the artist’s activity and correlating them with the fluctuating listenership, the algorithm aims to predict whether these actions will lead to an increase or decrease in popularity. The method considers various factors such as genre shifts, collaboration frequency, and engagement with current trends. Ultimately, this predictive model seeks to provide valuable insights for artists, record labels, and streaming platforms, aiding in strategic decision-making and audience engagement optimization.