  With the advent of smartphone technology, it has become possible to conceive
of entirely new classes of applications. Social swarming, in which users armed
with smartphones are directed by a central director to report on events in the
physical world, has several real-world applications: search and rescue,
coordinated fire-fighting, and the DARPA balloon hunt challenge. In this paper,
we focus on the following problem: how does the director optimize the selection
of reporters to deliver credible corroborating information about an event. We
first propose a model, based on common intuitions of believability, about the
credibility of information. We then cast the problem posed above as a discrete
optimization problem, and introduce optimal centralized solutions and an
approximate solution amenable to decentralized implementation whose performance
is about 20% off on average from the optimal (on real-world datasets derived
from Google News) while being 3 orders of magnitude more computationally
efficient. More interesting, a time-averaged version of the problem is amenable
to a novel stochastic utility optimization formulation, and can be solved
optimally, while in some cases yielding decentralized solutions. To our
knowledge, we are the first to propose and explore the problem of extracting
credible information from a network of smartphones.
