Recommendation Systems of Applications (RSA) are based on various types of user information. Some of these systems analyze the influence of social networks information in the installation of apps. However, these approaches do not include all the relevant user information. The present paper proposes a technique for recommending mobile applications based on a social and context information. The approach is compared with two existing techniques showing improvements in the recommendation quality and high tolerance to a small number of data.