The Living Labs are individually focused on particular domains of knowledge. Many of these domains are common to several Living Labs. To avoid multiple redundancies and improve the over-all performance, each Lab have to work in a collaborative way with all the specific knowledge communities which he belongs to, within the Living Labs global network. We propose to use our static and semantic model of social networks analysis to identify moving knowledge-sharing communities unit and actors - i.e. Living Labs and contributors. Our model enables the discovery and ranking of central or intermediate communities/actors involved in some knowledge domains named as keywords, within the global network. Then, it provides a way to find related or similar knowledge communities and actors. A first set of experiments is currently giving promising results in a commercial web agency application. Our work is funded by the French State Secretariat for prospective and development of the digital economy, in collaboration with a French IT services and software engineering company.