GoodWeb: use of social sensing to improve quality of life in cities and leverage new services

Abstract

Participatory sensor networks (RSPs), such as Instagram and Foursquare, allow the observation of the actions of hundreds of millions of people in urban areas in (almost) real-time and for long periods of time, thus being a source of social sensing. With that, our research is guided by the objectives of: (1) characterize and model patterns of urban social behavior and city dynamics with the help of different RSPs; and (2) explore the identified patterns for the proposal of new services and applications to facilitate the everyday life of users in the cities. From this perspective, a clear understanding of patterns of urban social behavior and city dynamics can lead to insights on mechanisms that contribute to the development of more sophisticated services and applications in the area of urban computing. The research proposed here aims at characterizing and modeling the patterns of urban social behavior and the dynamics of cities. Our particular interest is in cultural and urban displacement patterns, as well as factors that can be used to classify different geographic regions, and to help better understand user engagement. Moreover, this research also addresses the exploration of the patterns identified in new mechanisms and services, particularly new mechanisms for the study of large-scale cultural differences considering different aspects, new mechanisms to assist in the difficult task of classifying areas and new services and applications that make the lives of users in cities easier and more practical. (AU)