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The authors' CitySensing system captures at places social media streams and anonymous Call Data Records (CDR) during city-scale events. It semantically annotates the social media streams before fusing it with privacy-preserving aggregates of CDR. The result is analysed and repurposed to feed a public installation where visual story telling assumes a leading role in allowing the audience to perceive emerging patterns and to observe their dynamics. The authors demonstrate the efficacy of the visualization on the real-world data of two editions of Milan Design Week. This article is part of a special issue on social multimedia and storytelling.

Cities of the 21st century are places where various actors interact, where physical systems, that are sometime geographically distant, are strictly dependent, where relational mechanisms become crucial, and where the boundaries between individual and collective, local and global, real and digital become more and more blurred. In this context, social media can be used as a digital lens to analyze the space and the territory of cities. In fact, they offer a great opportunity to individualize and understand the connections that might exist between different spheres. In this article, we use Twitter to analyze the language mix of the city and to detect language communities within the city neighborhoods. We then compare these “digital” communities, discovered through Twitter, with the “real” communities identified by the traditional census data. Milan, a city which is increasingly becoming an international melting pot, is chosen as a case study for this work.

Cities are expanding and becoming more and more dynamic in terms of movement of population and, as a consequence, they are becoming melting pots with people of different cultures, religions and languages. In this paper, the authors use the multilingual analysis of Twitter to discover the "hidden cities" concealed within the city of Milan. Using the social media Twitter as a data source helps to detect weaker signals that are not captured through traditional census data. In this study, neighbourhoods in Milan are identified as areas where people speak mainly the same language on Twitter and these results are then compared with census data, to underline any parallelisms or discrepancies between the two sources of data. An added value of the paper is that the results are implemented within an online city dashboard, called Urbanscope.

Streams of information flow through our cities thanks to: their progressive instrumentation with diverse sensors, a wide adoption of smart phones and social networks, and a growing open release of datasets. City Data Fusion project investigates techniques to visualise the pulse of our cities in real-time by fusing and making sense of all those information flows. It exploits visual data analytics, semantic technologies, and streaming databases. In this poster, we offer insights on City Sensing: an early result of City Data Fusion that allows to visually analyse city scale events such as Milano Design Week.

In this chapter, we reflect upon how the urban experience is nowadays affected by data produced through interconnected, digital ecosystems such as the user-generated content on social media. We will present the scientific literature related to studies, research projects, and commercial platforms that use geo-located social mining techniques to extract urban knowledge. We will also analyze the state of the art in this thematic field and identify opportunities for further investigation.

In this chapter, we present our remarks on the design experiments we carried out and we illustrate how the possibilities of visualizing the data city offer a source of knowledge for urban planning and management that can help city stakeholders in important decisions. Some critical issues will also be addressed.

In this chapter, we present a series of design experiments conducted within the Telltale and Urban Sensing projects.