Ego-net digger: a new way to study ego networks in online social networks

Abstract

The vast proliferation of Online Social Networks (OSN) is generating many new ways to interact and create social relationships with others. While substantial results have been obtained in anthropology literature describing the properties of human social networks, a clear understanding of the properties of social networks built using OSN is still to be achieved. The presence of a huge amount of records containing users' communication history, provided by OSN, represents a new opportunity to analyse and better understand the human social behaviour. In this paper we present ego-net digger, a novel Facebook application for the analysis of ego networks in OSN. Ego-net digger collects users' social data and gives a representation of their personal social networks according to the Dunbar's circles model. To show the potential of our application we analyse a sample data set collected during a data acquisition campaign, finding interesting similarities between the structure of Facebook ego networks and the properties found in the anthropology literature. Specifically, we find that, in our sample, there is a clear evidence of the presence of the same ego network structure - i.e., the Dunbar's circles - as found in human social networks formed offline.