Extracting social networks from seized smartphones and web data

In this paper we propose an approach that allows one to get information about the social network of an individual by complementing the information provided by its (smart)phone with the data publicly available on the net. Our approach is based on a profile graph, whose nodes are the people involved and the (weighted) edges represent their mutual links. In a first phase, a preliminary version of the graph is built by using all the information available in the seized smartphone; later, the obtained graph is refined by mining publicly available data from the Web. Finally, the graph is clustered to generate cliques of people. All the phases of the process, described above, are performed by an integrated and interactive software tool, that allows the user to rapidly recover a smartphone\´s owner social network. Merging the information coming from the Web with the information stored on the mobile device allows to reach "clearer" results resolving homonimy problems by combining two different data sources, thus improving the precision of link weighting.