Talking Places: Modelling and Analysing Linguistic Content in Foursquare

Abstract

The advent of online social media and the growing popularity of sensor-equipped mobile devices have created a vast landscape of location-aware applications and services. This goldmine of data, including temporal and spatial information of unprecedented granularity, can help researchers gain insights into the behavioural patterns of people at a global scale. Here we analyse the textual content of millions of comments published alongside Foursquare user check-ins. For this, we extend a standard topic modelling approach so that it explicitly takes into account geographic and temporal side information. The framework is applied to Foursquare data and used to detect the dominant topics in the neighbourhoods of a city. In particular, we present the most prominent topics discussed by Foursquare users in New York, London, Chicago and San Francisco. We characterize the topics' spatial coverage and temporal evolution, and we also highlight some cultural idiosyncrasies. Finally, we evaluate the novel spatio-temporal topic model quantitatively. We believe that our model may be a useful tool for social scientists and application developers.