Evolutionary dynamics of the city brand influence of top ten global cities: Characteristics analysis driven by global news big data and intelligent semantic mining

Abstract

This study focuses on the long-term comparison of the city brand influence constructed and reflected by global news media. Specifically, from the analytical perspective of two paths and five characteristics, this study empirically and quantitatively assesses and deconstructs the evolutionary dynamics of the city brand influence of the top ten Globalization and the World Research Group (GaWC) Alpha+ or above global cities over five consecutive years based on intelligent semantic embedding mining on the Global Database of Events, Language, and Tone (GDELT) full-sample global news big data, along with statistical analysis and machine learning. The results indicate that the top ten global cities' city brand influence over five consecutive years fluctuated from high to low and then rebounded. The hierarchical tiers of the Alpha++ and Alpha+ global cities' city brand influence were relatively stable. However, there are inner tensions in the evolutionary trend, such as the uneven rank differences between the city brand influence soft power and the hard power of these cities, and the intersection of clustering categories between the Alpha++ and Alpha+ global cities. The findings and data of this study provide concrete references and guidelines for policymaking toward future competition of top global cities' city brand influence.