Toward a theoretical and substantial understanding of complex social Essay

Toward a theoretical and substantial understanding of complex societal networks - Essay ExampleThis research is being carried out to determine the viability of a theory. One of the best ways to do it is to compare it to the parameters and processes of real world systems. Aristotles examination of the physical manifestations of natural phenomena helped lead him to his theory of universals, which holds that an object has its own immutable and innate form a pear is a pear because it embodies that form. The observation of complex social networks, both great and small, yields invaluable learning about how their processes affect form, systemic characteristics and interact with other systems. The study of real-world networks reveals a wealth of information about the relevance of the random network model and the theory of scale-free networks, as developed by Albert-Laszlo Barabasi and Reka Albert. Thus, by observing systems such as food sack networks, human physiological systems and vari ous social interactions we may determine to what extent the laws of connectivity predict how they behave under certain circumstances. By extension, we may also employ systems that approximate real-world network tendencies, such as the worldwide web and power network grids. Both random and scale free networks exhibit characteristics that are recognizable in natural systems. In Linked The New Science of Networks, Barabasi and Albert describe random networks in terms of human physiology, explaining that the more links that are added at heart a system, the more difficult it becomes to find an isolated node. Thus the networks around and within us are very dense, which explains why all molecules in our corpse are integrated into a single complex cellular map (Barabasi and Albert 2002, p. 19). In this way, Nature creates redundancy to ensure survival by repeatedly and richly (exceeding) the one-link minimum (2002, p. 18). In developing the theory of scale-free network, Barabasi and Al bert found that most real-world networks display what they 2 describe as