ABSTRACT. The emergence of entangled urban networks is a salient feature of globalisation processes. Understanding the drivers behind the growth of such networks, and in particular urban firm networks, is crucial for the economic resilience of urban systems. We introduce in this paper a generative network model for firm networks at the urban area level, which includes several complementary processes which are the economic size of urban areas at origin and destination, industrial sector proximity between firms, the strength of links from the past as well as the geographical and socio-cultural distance. An empirical network analysis on European firm ownership data confirms a role for each factor. We then simulate network growth for synthetic systems of cities, unveiling stylized facts such as a transition from a local to a global regime or a maximal integration achieved at an intermediate interaction range. We finally calibrate the model on the European network, outperforming statistical models and showing a strong role of path-dependency. Potential applications of the model include the study of mitigation policies for exogenous shocks such as economic crisis.

ABSTRACT. We present an open-source interface for scientists to explore Twitter data through interactive network visualizations. Combining data collection, transformation and visualization in one easily accessible framework, the twitter explorer connects distant and close reading of Twitter data through the interactive exploration of interaction networks and semantic networks. By lowering the technological barriers of data-driven research, it aims to attract researchers from various disciplinary backgrounds and facilitates new perspectives in the thriving field of computational social science.