Aid is Out There: Looking for Help from Tweets during a Large Scale Disaster

Motoki Sano · Kentaro Torisawa · Chikara Hashimoto · Kiyonori Ohtake · Jong–Hoon Oh · Stijn De Saeger

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Public Relations and Crisis Communication Disaster Management and Resilience Topic Modeling

Abstract

The 2011 Great East Japan Earthquake caused a wide range of problems, and as countermeasures, many aid activities were carried out. Many of these problems and aid activities were reported via Twitter. However, most problem reports and corresponding aid messages were not successfully exchanged between victims and local governments or humanitarian organizations, overwhelmed by the vast amount of information. As a result, victims could not receive necessary aid and humanitarian organizations wasted resources on redundant efforts. In this paper, we propose a method for discovering matches between problem reports and aid messages. Our system contributes to problem-solving in a large scale disaster situation by facilitating communication between victims and humanitarian organizations.

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1971Measuring nominal scale agreement among many raters.2010Microblogging during two natural hazards events 2010Chatter on the red 2011Twitter for crisis communication: lessons learned from Japan's tsunami disaster 2009Online Community Response to Major Disaster: A Study of Tianya Forum in the 2008 Sichuan Earthquake

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2017Data-Driven Techniques in Disaster Information Management 2017Intelligent Disaster Response via Social Media Analysis A Survey 2021Automated Machine Learning Approaches for Emergency Response and Coordination via Social Media in the Aftermath of a Disaster: A Review 2019Extracting Resource Needs and Availabilities From Microblogs for Aiding Post-Disaster Relief Operations 2018Identifying Sub-events and Summarizing Disaster-Related Information from Microblogs 2016Applications of Online Deep Learning for Crisis Response Using Social Media Information 2018Graph Based Semi-Supervised Learning with Convolution Neural Networks to Classify Crisis Related Tweets 2019Using a combination of human insights and ‘deep learning’ for real-time disaster communication

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