\chapter{Introduction}
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\section{The objective}
The research project deals with the study of new paradigms for analyzing big data obtained from Location-Based Social Networks (but also where possible by sensors, participatory sensing and crowdsourcing), as a basis for the design and implementation of innovative infovis, browsing and recommendation systems for smart cities. Primary goals are the automatic identification of functional areas within cities through extraction of topics, user profiling, detection of macro and micro events and opinion mining. Various aspects have been addressed with an approach focused to knowledge fusion and semantics, still not adopted in the field of urban computing, with the objective of designing systems oriented to prediction and intervention-based analytics.

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\section{Contributions}
In this first year of my doctoral project I have resumed and continued some activities already underway at the Media Integration and Communication Center, University of Firenze, concerning the analysis of social data for user profiling and the identification of functional areas in cities, see Chapter~\ref{chap:urban-computing-fa}. I also designed and contributed to the implementation of a system for identification of micro-events in the streams themselves presented in Sec.~\ref{micro-events}. Another part of my activities has been focused on the design and development of applications of itineraries and events recommendation in urban environments. These applications (cfr. Sec.~\ref{roadie} and Sec. ~\ref{spherical-images}) exploit the techniques of user profiling presented in Sec.~\ref{user-profiling} and propose and provide original solutions for information visualisation.

}