An Examination of the Professional Football Industry in China: Insights Derived from Big Data Analysis

Abstract

This study investigates the critical challenges hindering the development of China's professional soccer industry through a big data analytical approach. Textual data were collected from major Chinese digital platforms between January 1, 2022, and October 31, 2024, and analyzed using TEXTOM, TF-IDF, sentiment analysis, and CONCOR techniques in UCINET6 and Netdraw. The findings show that financial instability, weak youth training systems, ineffective governance, and inconsistent policy implementation remain the most significant structural obstacles. Sentiment analysis further reveals strong public concern over financial transparency, coalition management, and the long-term sustainability of club operations. CONCOR analysis identifies fragmented policy execution and insufficient institutional coordination, indicating misalignment among governing bodies, clubs, and market actors. By integrating big data analytics with sport management research, this study provides a richer understanding of the systemic inefficiencies shaping China's professional soccer landscape. The results not only offer a novel methodological lens for examining industry transformation but also generate practical insights for policymakers and club administrators aiming to strengthen governance, enhance market mechanisms, and promote sustainable industry development.