/IP_Project-Social_analysis-1

Project which aims at studying the people' perceptions of a city (Turin) using their geo-tagged content published on the socials.

Primary LanguageJupyter Notebook

Automatic Urban functions identification via social analysis

We live in a connected world: more and more people share various moments of their daily lifeon social networks, mostly by posting photos, videos and descriptions. Consequently, every day billions of geo-referenced data are generated by user activities shaping what are generally known as digital footprints and providing inspiring insights about human activities and behaviors.

This research aims at studying the geographical contour of Turin in order to provide the administration a tool for capturing the users’ perception about the city. Through the analysis ofthe geo-tagged contents published on Flickr and Instagram, a pipeline comprehending clustering and classification techniques will provide a powerful link between the technology latent data andthe municipalities’ need for feedback and guidance to past and new investments.

The results show that both global studies about the city and specific investigations on particular zones and periods are feasible and reliable on respect to both our knowledge of the city and real indexes such as the cadastral value.