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In the last few years, a spectre has been haunting our academic and popular culture — the spectre of networks. Throughout social as well as natural sciences, more and more phenomena have come to be conceived as networks. Telecommunication networks, neural networks, social networks, epigenetic networks, ecological networks, value networks, the very fabric of our existence seems to be made of lines and points. More recently, the interest for graphs overflowed to popular culture and networks started to appear in art, graphics, advertizing, even furniture ADD OTHER EXEMPLES.  Our growing fascination for networks is not unjustified. Networks are powerful conceptual tools, encapsulating in a single object multiple affordances for the computation (networks as graphs), visualization (networks as maps) and manipulation of data (networks as interfaces).  In the first place and to a large extent, the success of networks is to be credited to the amazing versatility of graph mathematics. From railways to information routing, from financial to communications flows, from ecosystems to organization management graphs have found countless applications. Graph computational formalism proved so effective that we started seeing networks everywhere and transforming everything into systems of discrete but interconnected items. It would be unfair, however, to reduce networks to their mathematical properties. Graph theory has been around in mathematics since Euler’s walk on Königsberg’s bridges1, but it is not until the end of the last century that networks acquired a multidisciplinary popularity. Graph computation is certainly powerful, but it is also very demanding and for many years its advantages remained the privilege of scholars with solid mathematical bases.  In the last few decades, however, networks acquired a new set of affordances and reached a larger audience, thanks to the growing availability of tools to design them. Drawn on paper or screen, networks become easier to handle and obtain properties that calculation cannot express. Far from being merely aesthetic, the graphical representation of networks has an intrinsic hermeneutic value. Networks become maps and can be read as such.  Finally, the encounter with personal computing has recently turned networks into tools for data manipulation. Not only network-like visualizations are employed in a growing number of digital interfaces, but more and more specialized software has been designed to support the exploration of network data. Tools like Pajek (vlado.fmf.uni-lj.si/pub/networks/pajek), Ucinet (www.analytictech.com/ucinet), Guess (graphexploration.cond.org) and more recently Gephi (gephi.org) have progressively smooth out the difficulties of graph mathematics, turning a complex mathematical formalism in a simple point-and-click interface2.