Image4Act Online Social Media Image Processing for Disaster Response

We present an end-to-end social media image processing system called Image4Act. The system aims at collecting, denoising, and classifying imagery content posted on social media platforms to help humanitarian organizations in gaining situational awareness and launching relief operations. It combines...

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Bibliographic Details
Published in:2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) pp. 601 - 604
Main Authors: Alam, Firoj, Imran, Muhammad, Ofli, Ferda
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 31.07.2017
Series:ACM Conferences
Subjects:
Computing methodologies
Computing methodologies > Machine learning
Computing methodologies > Machine learning > Machine learning approaches
Computing methodologies > Machine learning > Machine learning approaches > Neural networks
Human-centered computing
Human-centered computing > Collaborative and social computing
Human-centered computing > Collaborative and social computing > Collaborative and social computing theory, concepts and paradigms
Human-centered computing > Collaborative and social computing > Collaborative and social computing theory, concepts and paradigms > Social media
Information systems
Information systems > Information retrieval
Information systems > Information retrieval > Retrieval tasks and goals
Information systems > Information retrieval > Retrieval tasks and goals > Sentiment analysis
Information systems > Information retrieval > Specialized information retrieval
Information systems > Information retrieval > Specialized information retrieval > Environment-specific retrieval
Information systems > Information systems applications
Information systems > World Wide Web
Information systems > World Wide Web > Web mining
Information systems > World Wide Web > Web mining > Data extraction and integration
ISBN:1450349935, 9781450349932
ISSN:2473-991X
Online Access:Get full text
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Summary:We present an end-to-end social media image processing system called Image4Act. The system aims at collecting, denoising, and classifying imagery content posted on social media platforms to help humanitarian organizations in gaining situational awareness and launching relief operations. It combines human computation and machine learning techniques to process high-volume social media imagery content in real time during natural and human-made disasters. To cope with the noisy nature of the social media imagery data, we use a deep neural network and perceptual hashing techniques to filter out irrelevant and duplicate images. Furthermore, we present a specific use case to assess the severity of infrastructure damage incurred by a disaster. The evaluations of the system on existing disaster datasets as well as a real-world deployment during a recent cyclone prove the effectiveness of the system.
ISBN:1450349935
9781450349932
ISSN:2473-991X
DOI:10.1145/3110025.3110164