On the use of participatory sensing to better understand city dynamics
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Prediction of user location using the radiation model and social check-ins
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
A comparison of Foursquare and Instagram to the study of city dynamics and urban social behavior
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
| Hi-index | 0.00 |
The pervasiveness of cell phones and mobile social media applications is generating vast amounts of geolocalized user-generated content. Since the addition of geotagging information, Twitter has become a valuable source for the study of human dynamics. Its analysis is shedding new light not only on understanding human behavior but also on modeling the way people live and interact in their urban environments. In this paper, we evaluate the use of geolocated tweets as a complementary source of information for urban planning applications. Our contributions are focussed in two urban planing areas: (1) a technique to automatically determine land uses in a specific urban area based on tweeting patterns, and (2) a technique to automatically identify urban points of interest as places with high activity of tweets. We apply our techniques in Manhattan (NYC) using 49 days of geolocated tweets and validate them using land use and landmark information provided by various NYC departments. Our results indicate that geolocated tweets are a powerful and dynamic data source to characterize urban environments.