Just-in-Time Social Cloud: Computational Social Platform to Guide People´s Just-in-Time Decisions

We present the design and development of the architecture of the just-in-time social cloud and experimental methods to measure the just-in-time social influences. Numerous studies have shown how social networks create social influences on people´s choices across time and space. We report on an empirical investigation of mobile social information on people´s decisions through the design and deployment of real world experiments. With the wide availability of social graph and social data accumulated through social networks, a just-in-time social cloud service framework can be designed to enable the applications to computationally filter people of similar activities and interests. Just-in-time social cloud service can better guide people toward their long term goals by influencing their choices at the moment and potentially mitigating behavioral biases. In order to measure the effects of the just-in-time social cloud, we identify the decision points where actual decisions or consideration of choices are made. Quasi-controlled experiments show that different manifestations of the social cloud result in varying outcomes in people´s choices. By deploying and experimenting in the real world, we find potential benefits and limitations of the just-in-time social cloud on people´s decisions. We delineate the different properties of the just-in-time social cloud experimentally and outline the contexts where the just-in-time social cloud can be beneficial.