A demographic analysis of online sentiment during hurricane Irene
LSM '12 Proceedings of the Second Workshop on Language in Social Media
Detection and extracting of emergency knowledge from twitter streams
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
Personalized emerging topic detection based on a term aging model
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Two weeks after the Great Tohoku earthquake followed by the devastating tsunami, we have sent open-ended questionnaires to a randomly selected sample of Twitter users and also analysed the tweets sent from the disaster-hit areas. We found that people in directly affected areas tend to tweet about their unsafe and uncertain situation while people in remote areas post messages to let their followers know that they are safe. Our analysis of the open-ended answers has revealed that unreliable retweets (RTs) on Twitter was the biggest problem the users have faced during the disaster. Some of the solutions offered by the respondents included introducing official hash tags, limiting the number of RTs for each hash tag and adding features that allow users to trace information by maintaining anonymity.