Abstract
This manuscript develops a GeoAI-based framework for measuring AI-related cooperation, competition, and innovation across global subnational regions using large-scale news data. It treats news events as relational evidence that can connect firms, public institutions, research organisations, technologies, and places.The planned workflow combines entity and location extraction, semantic classification, temporal network construction, and graph-based measures of regional position. It asks how AI-related activity is distributed across regions, how cooperation and competition networks evolve, and which places occupy brokerage or dependency positions in the emerging geography of artificial intelligence. Its abstract is accpted by an special issue in an economic geography journal.
The research links computational text analysis with economic-geography debates on regional capabilities, technological transitions, and uneven innovation.