SNA-based artificial Call Detail Records generator

Research involving Big Data often has to deal with the problem of data availability. Real-life data involving people and their activities is usually tied with various issues of privacy, security and secrecy, which results in difficult barriers which need to be overcome before the research can even start. In this paper we suggest an approach which can reliably provide researchers with an arbitrary amount of synthetic Call Detail Records (CDR) data which would exhibit a high level of similarity with a corresponding real-life dataset. We base our approach on a simulator whose functionality is derived on results of an exploratory analysis performed on a real-life dataset which represents a social network of users with records of their activities. In this paper we concentrate on generating CDR data used in telecommunications industry, although the approach is applicable in the other domains too.