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A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation
; Broad Institute of MIT and Harvard; Ronin Institute; Complex Biological Systems Alliance
Puni tekst: engleski, pdf (766 KB)
Banerjee, S. (2016). A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation. Interdisciplinary Description of Complex Systems : INDECS, 14(1). doi:10.7906/indecs.14.1.2
We inhabit a world that is not only “small” but supports efficient decentralized search – an individual using local information can establish a line of communication with another completely unknown individual. Here we augment a hierarchical social network model with communication between and within communities. We argue that organization into communities would decrease overall decentralized search times. We take inspiration from the biological immune system which organizes search for pathogens in a hybrid modular strategy.
Our strategy has relevance in search for rare amounts of information in online social networks and could have implications for massively distributed search challenges. Our work also has implications for design of efficient online networks that could have an impact on networks of human collaboration, scientific collaboration and networks used in targeted manhunts. Real world systems, like online social networks, have high associated delays for long-distance links, since they are built on top of physical networks. Such systems have been shown to densify i.e. the average number of neighbours that an individual has increases with time. Hence such networks will have a communication cost due to space and the requirement of building and maintaining and increasing number of connections. We have incorporated such a non-spatial cost to communication in order to introduce the realism of individuals communicating within communities, which we call participation cost.
We introduce the notion of a community size that increases with the size of the system, which is shown to reduce the time to search for information in networks. Our final strategy balances search times and participation costs and is shown to decrease time to find information in decentralized search in online social networks. Our strategy also balances strong-ties (within communities) and weak-ties over long distances (between communities that bring in diverse ideas) and may ultimately lead to more productive and innovative networks of human communication and enterprise. We hope that this work will lay the foundation for strategies aimed at producing global scale human interaction networks that are sustainable and lead to a more networked, diverse and prosperous society.
social computing; complex systems; social dynamics; innovation diffusion; artificial immune system
Hrčak ID: 152013
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