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We inhabit a world that is not only small but supports efficientdecentralized search - an individual using local information can establish aline of communication with another completely unknown individual. Here weaugment a hierarchical social network model with communication between andwithin communities. We argue that organization into communities would decreaseoverall decentralized search times. We take inspiration from the biologicalimmune system which organizes search for pathogens in a hybrid modularstrategy. Our strategy has relevance in search for rare amounts of informationin online social networks. Our work also has implications for design ofefficient online networks that could have an impact on networks of humancollaboration, scientific collaboration and networks used in targeted manhunts.Real world systems, like online social networks, have high associated delaysfor long-distance links, since they are built on top of physical networks. Suchsystems have been shown to densify. Hence such networks will have acommunication cost due to space and the requirement of maintaining connections.We have incorporated such a non-spatial cost to communication. We introduce thenotion of a community size that increases with the size of the system, which isshown to reduce the time to search for information in networks. Our finalstrategy balances search times and participation costs and is shown to decreasetime to find information in decentralized search in online social networks. Ourstrategy also balances strong-ties and weak-ties over long distances and mayultimately lead to more productive and innovative networks of humancommunication and enterprise. We hope that this work will lay the foundationfor strategies aimed at producing global scale human interaction networks thatare sustainable and lead to a more networked, diverse and prosperous society.

A Biologically Inspired Model of Distributed Online Communication Supporting Efficient Search and Diffusion of Innovation