This work proposes a software environment implementing a methodology for acquiring and exploiting the collective perception (CP) of Points of Interests (POIs) in a Smart City, which is meant to support decision makers in urban planning and management. This environment relies upon semantic knowledge discovery techniques and fuzzy computational approaches, including natural language processing, sentiment analysis, POI signatures and Fuzzy Cognitive Maps, turning them into a cohesive architectural blend in order to effectively gather the realistic perception of a user community towards given areas and attractions of a Smart City. The environment has been put to the test via a thorough experimentation against a massive user base of an online community with respect to a large metropolitan city (the City of Naples). Such an experimentation yielded consistent results, useful for providing decision makers with a clear awareness of the positive as well as critical aspects of urban areas, and thus helping them shape the measures to be taken for an improved city management and development.

Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Artificial Intelligence, Databases and Data Mining