The multiplex relations between cities
a lexicon-based approach to detect urban systems
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Abstract
Cities relate to other cities in many ways, and much scholarly effort goes into uncovering those relationships. Building on the principle that strongly related cities will co-occur frequently in texts, we propose a novel method to classify those toponym co-occurrences using a lexicon-based text-mining method. Millions of webpages are analysed to retrieve how 293 Chinese cities are related in terms of six types: industry, information technology, finance, research, culture and government. Each class displays different network patterns, and this multiplexity is mapped and analysed. Further refinement of this lexicon-based approach can revolutionize the study of inter-urban relationships.