The Wiki Music dataset: A tool for computational analysis of popular music

TL;DR

This paper introduces the Wiki Music dataset, a comprehensive resource for analyzing trends in popular music using statistical and machine learning methods to understand past patterns and predict future genres.

Contribution

The paper presents a handcrafted dataset with multi-faceted features annotated by genre and time, enabling advanced analysis of music evolution and genre prediction.

Findings

Identified trends in musical preferences over decades.

Successfully applied time series forecasting to predict future music genres.

Demonstrated the dataset's utility for computational music analysis.

Abstract

Is it possible use algorithms to find trends in the history of popular music? And is it possible to predict the characteristics of future music genres? In order to answer these questions, we produced a hand-crafted dataset with the intent to put together features about style, psychology, sociology and typology, annotated by music genre and indexed by time and decade. We collected a list of popular genres by decade from Wikipedia and scored music genres based on Wikipedia descriptions. Using statistical and machine learning techniques, we find trends in the musical preferences and use time series forecasting to evaluate the prediction of future music genres.