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Author (up) Sofia Eleni Spatharioti; Sara Wylie; Seth Cooper pdf 
  Title Does Flight Path Context Matter? Impact on Worker Performance in Crowdsourced Aerial Imagery Analysis Type Conference Article
  Year 2018 Publication ISCRAM 2018 Conference Proceedings 15th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2018  
  Volume Issue Pages 621-628  
  Keywords crowdsourcing; Amazon Mechanical Turk; context  
  Abstract Natural disasters result in billions of dollars in damages annually and communities left struggling with the difficult task of response and recovery. To this end, small private aircraft and drones have been deployed to gather images along flight paths over the affected areas, for analyzing aerial photography through crowdsourcing. However, due to the volume of raw data, the context and order of these images is often lost when reaching workers. In this work, we explored the effect of contextualizing a labeling task on Amazon Mechanical Turk, by serving workers images in the order they were collected on the flight and showing them the location of the current image on a map. We did not find a negative impact from the loss of contextual information, and found map context had a negative impact on worker performance. This may indicate that ordering images based on other criteria may be more effective.  
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  Corporate Author Thesis  
  Publisher Rochester Institute of Technology Place of Publication Rochester, NY (USA) Editor Kees Boersma; Brian Tomaszewski  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-0-692-12760-5 Medium  
  Track Social Media Studies Expedition Conference ISCRAM 2018 Conference Proceedings 15th International Conference on Information Systems for Crisis Response and Management  
  Notes spatharioti.s@husky.neu.edu Approved no  
  Call Number Serial 1584  
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