This article introduces some of the main concepts and methods of the science studying complex, self-organizing systems and networks, in a non-technical manner. Complexity cannot be strictly defined, only situated in between order and disorder. A complex system is typically modeled as a collection of interacting agents, representing components as diverse as people, cells or molecules. Because of the non-linearity of the interactions, the overall system evolution is to an important degree unpredictable and uncontrollable. However, the system tends to self-organize, in the sense that local interactions eventually produce global coordination and synergy. The resulting structure can in many cases be modeled as a network, with stabilized interactions functioning as links connecting the agents. Such complex, self-organized networks typically exhibit the properties of clustering, being scale-free, and forming a small world. These ideas have obvious applications in information science when studying networks of authors and their publications.
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