| Abstract |
Cities need to collect, store and process huge amounts of data in order to provide smarter services, such as mobility, traffic, and disaster management. Social networks, such as Twitter and Instagram, are participatory sensing systems where communities generate a large amount of data every day. Existing studies have been often focused on collecting and transforming social media data into insights that may help citizens, with no concern whether the dataset represents the phenomenon they want to understand. In this paper, we explore the adequacy of social networking services to be used as platforms for smart city applications. Here we propose a methodology composed of three steps and undertake a performance analysis with Twitter as a proof of concept. Our results show that in spite of well-known data delivery constraints of the Twitter Streaming API, the majority of tweets could be successfully captured with a delay that makes it adequate to real-time processing. |
