‘Big’ urban data are increasingly becoming accessible for scientific research and policy use. They may enhance the intelligence that is needed for understanding and mapping out social connectivity phenomena (in the sense of Jane Jacobs) in modern smart cities. The present paper aims to highlight and demonstrate the rich potential of information based on digital technology in modern cities. As a case study example of the power of social media data as a support tool in smart cities, we consider Twitter data in the municipality of Amsterdam. We use machine learning techniques to identify temporal patterns that we then relate back to their spatial dimension, effectively connecting the digital with physical aspect of cities. We also show that analysis of geo-referenced tweets can shed significant light on physical aspects of the city and on the spatial distribution of urban functions.
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