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Session 7b: Experiments
EC'17, June 26–30, 2017, Cambridge, MA, USA
Diffusion in Networks and the Unexpected Virtue of Burstiness
MOHAMMAD AKBARPOUR, Stanford University
MATTHEW JACKSON, Stanford University
Whether an idea, information, disease, or innovation diffuses throughout a society depends not only on
the structure of the network of interactions, but also on the timing of those interactions. Recent studies have
shown that diffusion can fail on a network in which people are only active in “bursts”, active for a while
and then silent for a while, but diffusion could succeed on the same network if people were active in a more
random Poisson manner. Those studies generally consider models in which nodes are active according to
the same random timing process and then ask which timing is optimal. In reality, people differ widely in
their activity patterns – some are bursty and others are not. We model diffusion on networks in which agents
differ in their activity patterns. We show that bursty behavior does not always hurt the diffusion, and in fact
having some (but not all) of the population be bursty significantly helps diffusion. We prove that maximizing
diffusion requires heterogeneous activity patterns across agents, and the overall maximizing pattern of agents’
activity times does not involve any Poisson behavior.
Additional Key Words and Phrases: Diffusion, Social Networks, Dynamic Networks, Heterogeneous Agents.
ACM Reference format:
Mohammad Akbarpour and Matthew Jackson. 2017. Diffusion in Networks and the Unexpected Virtue of
Burstiness. ACM Trans. Web 1, 1, Article 1 (June 2017), 1 pages.
Financial support from the NSF under grant SES-1155302 and from grant FA9550-12-1-0411 from the AFOSR and DARPA,
and ARO MURI award No. W911NF-12-1-0509. We thank Shayan Oveis Gharan for helpful conversations and Songyuan
Ding for coding some of the simulations reported here.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee
provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the
full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses,
contact the owner/author(s).
held Cambridge,
by the owner/author(s).
26–30, 2017,
Massachusetts, 1559-1131/2017/6-ART1
ACM ISBN 978-1-4503-4527-9/17/06.
ACM Transactions on Economics and Computation, Vol. 1, No. 1, Article 1. Publication date: June 2017.
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