AAAI Publications, Fifth AAAI Conference on Human Computation and Crowdsourcing

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Supporting Image Geolocation with Diagramming and Crowdsourcing
Rachel Kohler, John Purviance, Kurt Luther

Last modified: 2017-09-21

Abstract


Geolocation, the process of identifying the precise location in the world where a photo or video was taken, is central to many types of investigative work, from debunking fake news posted on social media to locating terrorist training camps. Professional geolocation is often a manual, time-consuming process that involves searching large areas of satellite imagery for potential matches. In this paper, we explore how crowdsourcing can be used to support expert image geolocation. We adapt an expert diagramming technique to overcome spatial reasoning limitations of novice crowds, allowing them to support an expert’s search. In two experiments (n=1080), we found that diagrams work significantly better than ground-level photos and allow crowds to reduce a search area by half before any expert intervention. We also discuss hybrid approaches to complex image analysis combining crowds, experts, and computer vision.

Keywords


crowdsourcing; geolocation; sensemaking; verification; journalism; diagramming; images; photos; videos; open source investigation

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