This research project aims to explore the concept of social meta-network, as a way of integrating social networks, such as Facebook, LinkedIn and others, providing an integrated perspective and transversal functionalities of added value for its users. The present approach uses graph databases, implemented using Neo4j. The nodes/vertices of the graph are used to represent people; properties on nodes are used to represent personal information of each individual; the relationships/edges represent directional relationships between individuals according to each social network; and the properties about relationships serve to maintain information about the relationship between individuals for each social network. The model created intends to be mixed solution focused on relationships by type of social network, referring details to the information existing in the native network itself. Native networks are seen as distinct dimensions in which the present solution makes it possible to relate information between these dimensions, even when there are no relationships between the networks/user in question. It also allows for a more complete perspective of each individual, integrating the professional, playful and other more specialized aspects, which leads to results that are much higher than what can be achieved by looking individually to each network - whether for problems/challenges of centrality/influence, identification and characterization of communities, identification of similarities, identification of potential relationships, among many other approaches. In practical terms, a huge asset for marketing purposes.
