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Most of the layout algorithms for clustered graphs have been designed to differentiate the groups within the graph, however they do not take into account the interactions between such groups. Identifying these interactions allows to understand how the different communities exchange messages or information, and allows the social network researcher to identify key actors, social roles and paths from one community to another. These interactions are performed by actors who actually share links with different communities. Thus, dividing the set of nodes into those who interact with several communities and those who only interact with their own communities, will give some insight about how the communities interact.