Network science is a subfield of complexity science devoted to the holistic analysis of complex systems through the study of the structure of networks that wire their components

• networks are pervasive in the real world: nature, society, information, and technology are supported by as many networks
• these networks are ostensibly different but in fact share an amazing number of interesting structural properties
• the main common feature shared by these networks is that they are webs without a spider: there exist no central authority that regulates their growth, but they evolve in a self-organized and decentralized way

1. Technological networks are physical networks that form the backbone of modern technological societies. These include:

   • Internet
   • telephone networks
   • power grids
   • transportation networks
   • distribution networks

2. Social networks are networks in which the nodes are people, or sometimes animals, and the edges represent some form of social interaction between them, such as love or friendship.

3. Information networks consist of items of data linked together in some way. Examples are:

   • World Wide Web
   • academic citation networks
   • peer-to-peer networks (like blockchains and IPFS)

4. Biological networks are widely used in many branches of biology as a convenient representation of patterns of interaction between appropriate biological elements. These biological networks include:

   • biochemical networks (like metabolic, protein-protein interaction, and genetic regularoty networks)
   • neural networks
   • ecological networks (like food webs)

Trees are hierarchical structures typically associated with the following principles:

• Centralism. The tree structure has a unique root node – the only node without a parent node higher in the hierarchy – from which all other nodes descend. This expresses a concentration of power and authority in a central actor of the system
• Finalism. It describes the unidirectional, linear courses of trees: any point in a tree is reachable from the root by a unique, linear, top-down path of intermediate nodes. Trees therefore embody an organization devoid of multilinearity or feedback loops

• a remarkable tree featured as a foldout frontispiece in a later 1780 edition of the French Encyclopédie, by Denis Diderot and Jean le Rond d’Alembert, first published in 1751.
• The Encyclopédie was a bastion of the French Enlightenment and one of the largest encyclopedias produced at that time. It consisted of 3,129 illustrations and 20 million words in 71,818 articles over 35 volumes
• the tree depicts a genealogical structure of knowledge, with its three prominent branches: memory and history (left), reason and philosophy (center), and imagination and poetry (right).

Networks are rhizomatic structures associated with the following principles:

• Decentralization. Networks are webs without a spider: there exist no central authority (root) that regulates their growth, but they evolve in a self-organized way
• Multilinearity. Networks allows feedback loops, that are paths that come back on their feet. This means that actors of the system can be reached through multiple paths

• this early hand-drawn image of a social network, taken from the work of psychiatrist Jacob Moreno, depicts friendship patterns between the boys (triangles) and girls (circles) in a class of schoolchildren in the 1930s
• this is the first example of a social network (or sociogram as it was called at the time) represented as a graph
• social network analysis (or sociometry) developed from this example in the field of social sciences, mainly during the 1960s. It is the mother of modern network science

RSA Animate - The Power of Networks from The RSA on Vimeo.