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Author (up) Muhammad Imran; Carlos Castillo; Jesse Lucas; Patrick Meier; Jakob Rogstadius pdf  isbn
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  Title Coordinating human and machine intelligence to classify microblog communications in crises Type Conference Article
  Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014  
  Volume Issue Pages 712-721  
  Keywords Information systems; Classification accuracy; Disaster response; Human intelligence; Large-scale datum; Machine computations; Machine intelligence; Real-world datasets; Supervised classifiers; Artificial intelligence  
  Abstract An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowd sourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real world datasets.  
  Address Qatar Computing Research Institute, Qatar; University of Madeira, Portugal  
  Corporate Author Thesis  
  Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9780692211946 Medium  
  Track Social Media in Crisis Response and Management Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 612  
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