Muhammad Imran
Carlos Castillo
Ji Lucas
ABSTRACT
We present AIDR (Artificial Intelligence for Disaster Response), a platform designed to perform automatic classification of crisis-related microblog communications. AIDR enables humans and machines to work together to apply human intelligence to large-scale data at high speed. The objective of AIDR is to classify messages that people post during disasters into a set of user-defined categories of information (e.g., "needs", "damage", etc.) For this purpose, the system continuously ingests data from Twitter, processes it (i.e., using machine learning classification techniques) and leverages human-participation (through crowdsourcing) in real-time. AIDR has been successfully tested to classify informative vs. non-informative tweets posted during the 2013 Pakistan Earthquake. Overall, we achieved a classification quality (measured using AUC) of 80%. AIDR is available at http://aidr.qcri.org/.
- S. R. Chowdhury, M. Imran, M. R. Asghar, S. Amer-Yahia, and C. Castillo. Tweet4act: Using incident-specific profiles for classifying crisis-related messages. In Proc. of ISCRAM, Baden-Baden, Germany, 2013.Google Scholar
- M. Imran, C. Castillo, J. Lucas, M. Patrick, and J. Rogstadius. Coordinating human and machine intelligence to classify microblog communications in crises. Proc. of ISCRAM, 2014.Google Scholar
- M. Imran, S. Elbassuoni, C. Castillo, F. Diaz, and P. Meier. Practical extraction of disaster-relevant information from social media. In Proc. of Workshop on Social Media Data for Disaster Management, WWW '13 Companion, pages 1021--1024. ACM/IW3C2, 20 Google ScholarDigital Library
- M. Imran, S. M. Elbassuoni, C. Castillo, F. Diaz, and P. Meier. Extracting information nuggets from disaster-related messages in social media. In Proc. of ISCRAM, Baden-Baden, Germany, 2013.Google Scholar
- M. Imran, I. Lykourentzou, and C. Castillo. Engineering crowdsourced stream processing systems. arXiv preprint arXiv:1310.5463, 2013.Google Scholar
- C. Li, J. Weng, Q. He, Y. Yao, A. Datta, A. Sun, and B.-S. Lee. Twiner: named entity recognition in targeted twitter stream. In Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, pages 721--730. ACM, 2012. Google ScholarDigital Library
- D. Turaga, H. Andrade, B. Gedik, C. Venkatramani, O. Verscheure, J. D. Harris, J. Cox, W. Szewczyk, and P. Jones. Design principles for developing stream processing applications. Software: Practice and Experience, 40(12):1073--1104, 2010. Google ScholarDigital Library
- S. Vieweg. Microblogged contributions to the emergency arena: Discovery, interpretation and implications. In Proc. of CSCW, February 2010.Google Scholar
- S. E. Vieweg. Situational awareness in mass emergency: A behavioral and linguistic analysis of microblogged communications. 2012.Google Scholar
Index Terms
- AIDR: artificial intelligence for disaster response
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