Developing a Semantic Content Analyzer for L'Aquila Social Urban Network

This paper presents the preliminary results of a joint research project about Smart Cities. This project is adopting a multidisciplinary approach that combines artificial intelligence techniques with psychology research to monitor the current state of the city of L’Aquila after the dreadful earthquake of April 2009. This work focuses on the description of a semantic content analysis module. This component, integrated into L’Aquila Social Urban Network (SUN), combines Natural Language Processing (NLP) and Artificial Intelligence (AI) to deeply analyze the content produced by citizens on social platforms in order to map social data with social indicators such as cohesion, sense of belonging and so on. The research carries on the insight that social data can supply a lot of information about latent people feelings, opinion and sentiments. Within the project, this trustworthy snapshot of the city is used by community promoters to proactively propose initiatives aiming at empowering the social capital of the city and recovering the urban structure which has been disrupted after the ’diaspora’ of citizens in the so called ”new towns”. 1 L’Aquila Social Urban Network: a hybrid city model The city of L’Aquila is located in the mountain region of Abruzzi, in central Italy. In 2009 the life of this town has been seriously modified by an earthquake that caused damage to between 3.000 and 11.000 buildings in the medieval city of L’Aquila. 297 people died in the earthquake. The severe trauma to physical and psycho-social structures is still in the phase of recovery, since the urban centre has not been fully restored and almost half of all citizens still are displaced from their pre-earthquake homes. The specificity of the situation represent a perfect scenario where the principles and the insights behind the concept of 7 This paper summarizes the results already presented in the AI*IA 2013 workshop on Smart Cities URL: http://ai.unibo.it/SmartCityAIIA2013