Abstract
In this chapter we propose a framework for collecting, organizing into a database and querying information in social networks by the specification of content-based, geographic and temporal conditions to the aim of detecting periodic and aperiodic events. Our proposal could be a basis for developing context aware services.
For example to identify the streets and their rush hours by analyzing the messages in social media periodically sent by queuing drivers and to report these critical spatio-temporal situations to help other drivers to plan alternative routes. Specifically, we rely on a focused crawler to periodically collect messages in social networks related with the contents of interest, and on an original geo-temporal clustering algorithm in order to explore the geo-temporal distribution of the messages.
The clustering algorithm can be customized so as to identify aperiodic and periodic events at global or local scale based on the specification of geographic and temporal query conditions.