Lines of research

[1] Key public spaces retrieved from Foursquare data [Foursquare]
This project identifies which are the most popular public spaces and activities of the city through the use of social network data. Foursquare data can be used to understand citizen preferences over city spaces and the most popular economic activities of a given urban area.

[2] Exploring temporality and seasonality of city spaces [Twitter]
The objective of this project is to determine the extent to which temporality and seasonality influence the social processes and liveliness of the city. These time-spatial variables shed light on the identity and character of the urban environment and its significance for society. Twitter provides up to date information about the geoposition of people at different times of the day. Thus, by mapping datasets retrieved from this social network we are able to read patterns of social behaviour within a city.

[3] Mapping urban complexity and patterns of economic activity in contemporary cities: virtual world vs. reality [Google Places]
Functional areas of the city can be identified by studying the variety of economic activities offered . From the study of commercial activity using data from web services such as Google Places, the virtual reality is depicted as  an economic layer of a city. The relationship between this information and the actual physical reality show correspondences and discrepancies between the city and its virtual image.

[4] Addressing urban perception through social networks [Panoramio]
This research line aims to understand how the urban environment is perceived by analysing the geo-tagged pictures shared by citizens. The use of images for communicating through the network can illustrate the social perception of places in our cities and depict the character of most relevant urban landscapes.

[5] Analysing perception and interaction with urban spaces  [Instagram]
Instagram provides data based on a dynamic time frame that is constantly being updated. In this research line, Instagram images are not only analysed for their composition or their intention, but also, since they include geotagged data —hashtags and comments—, the perception and people’s interaction with urban spaces are studied.