The ubiquitous availability of computing technology such as smartphones, tablets, and other easily portable devices, and the worldwide adoption of social networking sites make it increasingly possible for one to be connected and continuously contribute to this massively distributed information publishing process. In this scenario, people act as social sensors, voluntarily providing data that capture their daily life experiences, and offering diverse observations on both the physical world (e.g., location) and the online world (e.g., events). This large amount of social data can provide new forms of valuable information that are currently not available on this scale via any traditional data collection methods, and can be used to enhance decision making processes. In this article, we argue that location-based social media systems, such as Instagram and Foursquare, can act as valuable sources of large-scale sensing, providing access to important characteristics of urban social behavior much more quickly than traditional methods. We also discuss different applications and techniques that can exploit the data shared in these systems to enable large-scale and nearreal- time analyses and visualization of different aspects of city dynamics.
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