Optimizing Information Credibility in Social Swarming Applications

TL;DR

This paper introduces a novel approach to optimize the selection of smartphone reporters in social swarming applications to maximize information credibility, offering efficient algorithms and a new stochastic utility framework.

Contribution

It is the first to formulate and solve the problem of extracting credible information from smartphone networks using centralized, approximate, and stochastic optimization methods.

Findings

Approximate decentralized solution performs within 20% of optimal.

Proposed algorithms are three orders of magnitude more efficient.

Time-averaged problem admits an optimal stochastic utility solution.

Abstract

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.