Unveiling the Listener Structure Underlying K-pop's Global Success: A Large-Scale Listening Data Analysis

2025-09-08

AI Summary

This study investigates how K-pop evolved from a regional Asian genre into a global music phenomenon, focusing on shifts in audience composition and dissemination mechanisms. Method: Leveraging large-scale listening logs (2005–2019) from Last.fm, we employ playback frequency distribution analysis, Gini coefficient measurement, and semantic evolution analysis of user-generated tags to quantify K-pop’s global adoption trajectory. Contribution/Results: We find that K-pop’s popularity is disproportionately driven by a small cohort of heavy listeners—evidenced by a significantly higher Gini coefficient than both mainstream and niche genres—exhibiting a “sparse long tail, polarized head” participation pattern. Concurrently, tag semantics evolve from geographically anchored terms (e.g., “Korea,” “Asian”) toward de-territorialized, genre-specific labels (e.g., “Kpop,” “BTS”), signaling a symbolic transition from a geographic descriptor to an autonomous global genre. This study provides the first large-scale empirical account of the core drivers and identity-construction mechanisms underpinning K-pop’s globalization.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Machine Learning: Learning Preferences or Rankings

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Web Mining and Content Analysis: Content-based information diffusion
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Abstract

From the mid-2000s to the 2010s, K-pop moved beyond its status as a regionally popular genre in Asia and established itself as a global music genre with enthusiastic fans around the world. However, little is known about how the vast number of music listeners across the globe have listened to and perceived K-pop. This study addresses this question by analyzing a large-scale listening dataset from Last.fm. An analysis of the distribution of play counts reveals that K-pop experienced a significant increase in plays between 2005 and 2019, largely supported by a small group of heavy listeners. The Gini coefficient in play counts is notably greater than that of existing mainstream genres and other growing niche genres. Furthermore, an analysis based on user-assigned genre tags quantitatively demonstrates that between 2005 and 2010, K-pop shed its status as a local Asian genre and established itself as a distinct music genre in its own right.

Problem

• Analyzing global K-pop listener structure using large-scale data
• Investigating play count distribution and listener engagement patterns
• Examining genre perception shifts through user-assigned tags

Innovation

• Analyzed large-scale Last.fm listening dataset
• Used Gini coefficient to measure play distribution inequality
• Quantified genre evolution through user-assigned tags