Abstract
Understanding how people communicate during disasters is important for creating systems to support this communication. Twitter is commonly used to broadcast information and to organize support during times of need. During the 2010 Gulf Oil Spill, Twitter was utilized for spreading information, sharing firsthand observations, and to voice concern about the situation. Through building a series of classifiers to detect emotion and sentiment, the distribution of emotion during the Gulf Oil Spill can be analyzed and its propagation compared against released information and corresponding events. We contribute a series of emotion classifiers and a prototype collaborative visualization of the results and discuss their implications.
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© 2014 Springer International Publishing Switzerland
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Torkildson, M.K., Starbird, K., Aragon, C. (2014). Analysis and Visualization of Sentiment and Emotion on Crisis Tweets. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2014. Lecture Notes in Computer Science, vol 8683. Springer, Cham. https://doi.org/10.1007/978-3-319-10831-5_9
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DOI: https://doi.org/10.1007/978-3-319-10831-5_9
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10830-8
Online ISBN: 978-3-319-10831-5
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