Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Twitter in mass emergency: what NLP techniques can contribute
WSA '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media
Twitter under crisis: can we trust what we RT?
Proceedings of the First Workshop on Social Media Analytics
Mining conversations of geographically changing users
Proceedings of the 21st international conference companion on World Wide Web
On-site information seeking behaviors in earthquake and tsunami
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Regional analysis of user interactions on social media in times of disaster
Proceedings of the 22nd international conference on World Wide Web companion
Faking Sandy: characterizing and identifying fake images on Twitter during Hurricane Sandy
Proceedings of the 22nd international conference on World Wide Web companion
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The Great Eastern Japan Earthquake, which struck Japan on March 11, catastrophically affected all aspects of life: buildings, power plants, human life, etc. Moreover, it caused severe problems related to network infrastructure. We can ascertain the degree of network disorder from network traffic logs. Although we can infer what people did when the earthquake occurred on the Web from network traffic logs, we cannot know it precisely. Social media were used effectively during and after this earthquake, and they left a partial log revealing what people did on the Web during and after the earthquake. Such a log is one of the first logs of people's actions in a time of a catastrophic disaster. As described in this paper, we analyze Twitter logs and attempt to extract what happened in the emergency situation.