  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. 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. Hence such networks will have a
communication cost due to space and the requirement of maintaining connections.
We have incorporated such a non-spatial cost to communication. 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 and weak-ties over long distances 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.
