Abstract: Systems and methods are provided for generating recommendations for users of a service. A data processor collects raw user data and provides that data to a learning engine. The learning engine analyzes the data to generate weighted social aspect scores and further to generate a social affinity score using the weighted social aspect scores. The social affinity score is combined with information about people near the user to generate a social context, and the availability of the user is evaluated to determine whether a recommendation should be provided to the user.