In this paper we present constructive algorithms for generating realistic synthetic ego networks (one of the most important representations of human social networks). These algorithms are based on ego network models derived in the anthropology literature, which describe the key structural properties of ego networks, and the properties of the social relationships between individuals. The main area we consider for applying these algorithms is the study of social networking environments currently under discussion in the research community. In particular, we focus on two relevant examples, i.e. Mobile Social Networks, and Social Pervasive Networks. In both cases, together with the ego network structural properties, it is fundamental to also describe the statistical properties of the contact process between the nodes. To this end, we complement the algorithms with an analytical model that characterises the dependence between the key distributions used in the literature to describe the contact processes. Finally, we validate our algorithms and models, showing that the synthetic ego networks that can be generated matches both structural properties of ego networks, and contact process properties that have been found in real human social networks.