Interest in networks visualization continues to grow, as new uses and tools emerge. Among the networks that are more interesting and useful to visualize are the ones coming from humanities and cultural contexts, since these contexts have a tradition of working with relational logics and information (rather than quantitative ones). The metaphor of culture and humanities as networks precedes by far the practice of visualizing them. In this young field, however, there are many common problems and unsolved challenges, such as the fact that network visualizations tend to be good at displaying overall and abstract patterns, or helping identifying very local facts, but are poor building structured narratives. There exist two main visualization strategies: the global one, that often reproduces a shape known as hairball, in which relations are unreadable; and the local one, that gives rich information about specific relations yet loosing the context.
I propose a series of advanced interactive techniques that connect the local view and the global view, and that build narratives out of subsets of nodes: partial linearities out of the non-linearity. My techniques, based on graph theory and geometrical algorithms, include the use of interactive back and forth transitions between local and global views, simulations and stimulations that help to understand the spread of influences among nodes, and the use of the “reenactment mode” in which dynamical and temporal behaviors are reproduced in a way new stories are created. By using these techniques the interactor has a complete experience of exploration and obtains insight from local, global and intermediate scales. Cultural networks often come from very dynamic realties such as creative dialogues, influences and co-operations that lay extended in time, the reenactment strategy reconstructs and visualizes these processes, and thus conveys these dynamic human realities.