One emerging and challenging issue in Smarter Cities is Mobility. In order to gather mobility data for relevant analyses, two solutions are widely discussed, namely the conventional standardized infrastructure sensors and the novel social sensing solution. However infrastructure sensors solution is too costly, that is unfeasible for every city. On the contrast, social sensing is a renewal approach, by which people perform “sensory data” collection tasks. In order to widely conduct the second solution and meet various needs of cities, it requires the ability to 1) support various social data sources, 2) be scalable, customizable and configurable, and 3) use cost-efficient IT resources. However current research cannot overcome these challenges. Therefore, this paper presents a social sensing data analysis framework in cloud for smarter cities, especially to support smart mobility. As a case study, Mobility Analyzer, a subsystem of IRMA (Integrated Real-time Mobility Assistant, that is a pilot project of Pavia, Italy), is implemented.